{"id":1656,"date":"2026-07-27T01:44:21","date_gmt":"2026-07-26T20:14:21","guid":{"rendered":"https:\/\/www.editage.com\/blog\/?p=1656"},"modified":"2026-07-29T08:08:35","modified_gmt":"2026-07-29T02:38:35","slug":"how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations","status":"publish","type":"post","link":"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/","title":{"rendered":"How to Use AI to Write a Case Report: Prompts, Examples, and Tips to Avoid Hallucinations"},"content":{"rendered":"<p><strong>Highlights:<\/strong><\/p>\n<ul>\n<li>AI tools, especially large language models (LLMs), can speed up drafting a case report.<\/li>\n<li>They are not able to effectively spot logical flaws, unclear novelty or weak implications for practice.<\/li>\n<li>A human editor can improve flow, coherence, and technical word choice in an AI-generated manuscript.<\/li>\n<li>An optimum workflow for busy clinicians is to use AI to generate a first draft, verify the accuracy of the AI output, and then have the manuscript checked by a subject-matter expert editor who also ensures adherence to your target journal\u2019s guidelines.<\/li>\n<li>Always upload deidentified data into an AI tool and get confirmation beforehand that it\u2019s okay to use that tool for writing.<\/li>\n<\/ul>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#What_AI_Is_Good_At\" >What AI Is Good At<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Example_turning_clinical_notes_into_academic_writing_suitable_for_a_journal\" >Example: turning clinical notes into academic writing suitable for a journal<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Where_the_AI_Draft_Falls_Short\" >Where the AI Draft Falls Short<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#1_Flow_across_the_whole_manuscript_not_just_within_paragraphs\" >1. Flow across the whole manuscript, not just within paragraphs<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#2_Logical_inconsistencies_the_model_wont_flag\" >2. Logical inconsistencies the model won\u2019t flag<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#3_Correct_use_of_technical_terms_in_context\" >3. Correct use of technical terms in context<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#4_Whether_novelty_and_teaching_value_are_clearly_presented\" >4. Whether novelty and teaching value are clearly presented<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Example_sharpening_the_teaching_point\" >Example: sharpening the teaching point<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#A_Practical_Workflow_for_Using_AI_to_Write_Case_Reports\" >A Practical Workflow for Using AI to Write Case Reports<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#What_the_Researcher_Must_Do_Before_Using_AI_to_Draft\" >What the Researcher Must Do Before Using AI to Draft<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Strong_vs_Weak_Prompts_for_AI-Drafted_Case_Reports\" >Strong vs. Weak Prompts for AI-Drafted Case Reports<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#How_to_Avoid_Hallucinations_When_Using_AI_to_Write_a_Case_Report\" >How to Avoid Hallucinations When Using AI to Write a Case Report<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Before_drafting\" >Before drafting<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#While_drafting\" >While drafting<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#After_drafting\" >After drafting<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#The_Ethics_of_Uploading_Patient_Data_into_AI_Tools\" >The Ethics of Uploading Patient Data into AI Tools<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Aligning_the_Case_Report_with_Journal_Requirements\" >Aligning the Case Report with Journal Requirements<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Example_1_Blood\" >Example 1: Blood<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Example_2_BMJ_Case_Reports\" >Example 2: BMJ Case Reports<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Example_3_European_Heart_Journal_%E2%80%93_Case_Reports\" >Example 3: European Heart Journal &#8211; Case Reports<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#The_Role_of_a_Medical_Editor_in_Case_Report_Formatting\" >The Role of a Medical Editor in Case Report Formatting<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#How_to_Avoid_Journal_Rejection_for_Using_AI\" >How to Avoid Journal Rejection for Using AI<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Disclosure\" >Disclosure<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Authorship\" >Authorship<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-26\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Content_and_originality\" >Content and originality<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-27\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Data_and_consent\" >Data and consent<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-28\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Bottom_Line\" >Bottom Line<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-29\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-30\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Do_I_need_to_disclose_that_I_used_AI_like_ChatGPT_to_write_my_case_report\" >Do I need to disclose that I used AI (like ChatGPT) to write my case report?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-31\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Can_ChatGPT_or_another_AI_be_listed_as_a_co-author_on_a_case_report\" >Can ChatGPT or another AI be listed as a co-author on a case report?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-32\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Will_journals_reject_a_case_report_because_it_was_drafted_with_AI\" >Will journals reject a case report because it was drafted with AI?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-33\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Is_using_AI_to_write_a_medical_case_report_considered_plagiarism\" >Is using AI to write a medical case report considered plagiarism?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-34\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#How_do_I_cite_or_reference_an_AI_tool_like_ChatGPT_in_a_case_report\" >How do I cite or reference an AI tool like ChatGPT in a case report?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-35\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#How_much_of_a_case_report_can_be_AI-generated_before_its_a_problem\" >How much of a case report can be AI-generated before it\u2019s a problem?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-36\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Can_AI-generated_case_reports_contain_fake_or_%E2%80%9Challucinated%E2%80%9D_citations\" >Can AI-generated case reports contain fake or \u201challucinated\u201d citations?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-37\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/#Do_I_need_patient_consent_if_I_use_AI_to_help_write_their_case_report\" >Do I need patient consent if I use AI to help write their case report?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><a name=\"_Toc235646527\"><\/a>Introduction<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><a href=\"https:\/\/www.editage.com\/blog\/what-is-a-case-report-format-checklist-and-examples\/\">Case reports<\/a> are one of the easiest articles that a busy medical researcher can write, and also one of the hardest to get published. A good case report cannot just describe what happened to a patient. It has to give another clinician something genuinely new to learn from it.<\/p>\n<p>Large language models (LLMs) are now very good at the mechanical parts of getting a case report onto the page: fixing <a href=\"https:\/\/www.editage.com\/blog\/common-grammar-mistakes\/\">grammar<\/a>, formulating sentences, organizing the standard sections, and producing a clean first draft from rough notes. But they are not reliable for judging whether the case actually teaches anything, whether the clinical logic holds together, and whether the manuscript reads the way an experienced reviewer expects a case report to read. That gap is where a human editor, with experience in medical publishing, becomes very important.<\/p>\n<p><em>See also: <a href=\"https:\/\/www.editage.com\/blog\/what-is-a-case-report-format-checklist-and-examples\/\">What is a Case Report? Format, Tips, Examples<\/a><\/em><\/p>\n<p>This article explains what AI genuinely handles well when drafting a case report, where a human pass adds real value, how to avoid AI hallucinations in your case report, and the ethics of putting patient information into an AI tool in the first place.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_AI_Is_Good_At\"><\/span><a name=\"_Toc235646528\"><\/a>What AI Is Good At<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Modern AI academic writing assistants are reliable for the parts of writing that are essentially mechanical: converting a clinician\u2019s rough, note-form account of a case into full sentences; ensuring no grammar or punctuation errors; fine-tuning tone and style; and ensuring consistent headings. AI is also useful for producing a first pass at abstracts.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Example_turning_clinical_notes_into_academic_writing_suitable_for_a_journal\"><\/span>Example: turning clinical notes into academic writing suitable for a journal<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Raw input from a clinician might look like this:<\/p>\n<p>\u201c58F, 3 days chest pain, worse breathing, hx breast ca 2019 treated, came to ED, ECG normal, d-dimer high, CT showed PE bilateral, started on apixaban, discharged day 4.\u201d<\/p>\n<p>An LLM can turn this into: \u201cA 58-year-old woman with a history of breast cancer treated in 2019 and in remission presented to the emergency department with a 3-day history of chest pain and worsening dyspnea. Her electrocardiogram was unremarkable, but D-dimer was elevated. Computed tomography pulmonary angiography demonstrated bilateral pulmonary emboli. She was started on apixaban and discharged on day 4.\u201d<\/p>\n<p>This is a genuine time saver. The sentence structure, tense, and flow are all correct, and nothing here required clinical judgment beyond faithfully transcribing what was said.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Where_the_AI_Draft_Falls_Short\"><\/span><a name=\"_Toc235646529\"><\/a>Where the AI Draft Falls Short<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"1_Flow_across_the_whole_manuscript_not_just_within_paragraphs\"><\/span>1. Flow across the whole manuscript, not just within paragraphs<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>AI drafts tend to read well sentence by sentence but can feel disjointed at the level of the whole report. A common failure is repeating the same clinical detail in both the case presentation and the discussion in near-identical wording, or introducing the teaching point of the case too late, after the reader has already lost interest.<\/p>\n<p>A human editor reading start to finish can restructure so that the discussion builds on the case rather than re-describing it, and can move the sentence that states why the case matters into the first paragraph, where an editor and reader will actually look for it.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"2_Logical_inconsistencies_the_model_wont_flag\"><\/span>2. Logical inconsistencies the model won\u2019t flag<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>An LLM will not usually notice that a stated timeline doesn\u2019t add up or that a treatment decision doesn\u2019t follow from the findings described.<\/p>\n<p>Let\u2019s take the example of a draft describing a patient at 32 weeks\u2019 gestation who presents with reduced fetal movement: one paragraph states that amniotic fluid index was 16 cm (in the reference range), and then the next paragraph states that the patient was admitted for an emergency Cesarean section owing to oligohydramnios. Both sentences are individually well formed, so an AI tool is likely to let the contradiction pass and won\u2019t point out that the stated indication for Cesarean delivery doesn\u2019t match the finding reported earlier in the same case. A human reader with clinical knowledge is far more likely to notice the contradiction, because catching it requires understanding the whole clinical picture and not just checking each sentence for grammar.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"3_Correct_use_of_technical_terms_in_context\"><\/span>3. Correct use of technical terms in context<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>LLMs frequently use medical terms fluently but not always precisely. For example, they may treat sensitivity and specificity as loosely interchangeable in a sentence about a screening test. Another frequent issue is loose staging or grading language, for example, describing a tumor as advanced without citing the actual stage, or using \u201cmild\u201d and \u201cmoderate\u201d inconsistently across a report describing severity. A subject-matter expert reviewing the draft is the only reliable check for this kind of precision, because the error is invisible to a grammar check and often invisible to the model itself.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"4_Whether_novelty_and_teaching_value_are_clearly_presented\"><\/span>4. Whether novelty and teaching value are clearly presented<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Journals accept case reports for a narrow set of reasons: an unexpected presentation, a diagnostic pitfall, an unusual complication, a rare drug interaction, or a management approach that goes against the usual pathway. An AI draft will dutifully describe the case but rarely makes the explicit argument for why it is worth publishing.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Example_sharpening_the_teaching_point\"><\/span>Example: sharpening the teaching point<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The first sentence of the discussion of a case report generated by AI reads as follows:<\/p>\n<p><em>\u201cThis case sheds light on the underlying causes of jaundice in neonates who present with prolonged severe hyperbilirubinemia.\u201d<\/em><\/p>\n<p><strong>Comment [Editor]:<\/strong> This is sentence is grammatically correct, but it reads like a generic reminder to examine the causes of jaundice. Consider adding more details here to clarify what this case teaches other neonatologists.<\/p>\n<p><strong>Comment [Author]:<\/strong> Everyone assumed breastfeeding jaundice. We almost decided to not check bilirubin levels at the 3-week visit because he was exclusively breastfed and had gained weight. That\u2019s something other clinicians should be aware of.<\/p>\n<p><strong>Comment [Editor]:<\/strong> Thank you for this clarification. Please check if the following revision captures what you were trying to convey:<\/p>\n<p><strong>Final edited version:<\/strong> <em>\u201cThis case is notable because the infant\u2019s jaundice persisted well beyond the 14-day cutoff for physiological jaundice, yet was initially managed as routine breastfeeding jaundice without further work-up as the infant was gaining weight appropriately. The eventual diagnosis of biliary atresia illustrates why neonatologists who observe prolonged severe jaundice past 14 days of life in an exclusively breastfed infant should refer the infant for conjugated bilirubin measurement.\u201d<\/em><\/p>\n<p>The final edited version says something specific and arguable. The AI-generated version is true of almost any neonatal jaundice case and would not teach a neonatologist anything that isn\u2019t already covered in a textbook. (Note that the editor got information regarding the diagnosis and conjugated bilirubin measurement from elsewhere in the manuscript. The editor also verified that the previous sections had already mentioned that the infant was exclusively breastfed and that his weight gain had been documented.)<\/p>\n<h2><span class=\"ez-toc-section\" id=\"A_Practical_Workflow_for_Using_AI_to_Write_Case_Reports\"><\/span><a name=\"_Toc235646530\"><\/a>A Practical Workflow for Using AI to Write Case Reports<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A workable approach is to let AI handle the first structural draft: converting notes into prose, applying standard case report formatting, and producing a readable abstract. The next step should be a careful check for accuracy, cross-verifying all data against the patient\u2019s chart, diagnostic imaging, etc. Finally, run the manuscript by a professional medical editor who focuses specifically on four questions:<\/p>\n<ol>\n<li>Does the manuscript flow as a single argument rather than a list of facts?<\/li>\n<li>Is the clinical reasoning internally consistent from presentation through to discussion?<\/li>\n<li>Is every technical term used correctly and precisely?<\/li>\n<li>Is the reason this case deserves publication stated explicitly and early?<\/li>\n<\/ol>\n<p>None of these four aspects can be checked by asking an AI tool to proofread or improve a draft.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"What_the_Researcher_Must_Do_Before_Using_AI_to_Draft\"><\/span>What the Researcher Must Do <em>Before<\/em> Using AI to Draft<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<table>\n<thead>\n<tr>\n<td><strong>Step<\/strong><\/td>\n<td><strong>Action<\/strong><\/td>\n<td><strong>Why It Matters<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>1<\/td>\n<td><strong>Obtain informed consent<\/strong> from the patient (or legal guardian) specifically for publication of their case, per journal\/CARE guideline requirements<\/td>\n<td>Standard ethical requirement for any case report, independent of AI use<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td><strong>De-identify all data<\/strong> (names, dates, MRNs, geographic identifiers, rare identifying details) <em>before<\/em> it touches any AI tool<\/td>\n<td>Prevents personal health information exposure via a third-party system; required under HIPAA\/GDPR-equivalent rules<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td><strong>Check institutional and journal policy on AI use:<\/strong> whether AI-assisted drafting is permitted, and what disclosure is required<\/td>\n<td>Many journals (e.g., ICMJE-aligned) mandate <a href=\"https:\/\/www.editage.com\/blog\/how-to-write-an-ai-disclosure-statement-examples-and-format-for-journal-articles-and-dissertations\/\">disclosure of AI tool use<\/a> in <a href=\"https:\/\/www.editage.com\/blog\/methods-section-research-paper\/\">methods<\/a>\/<a href=\"https:\/\/www.editage.com\/blog\/how-to-write-the-acknowledgments-section-of-a-research-paper-examples-and-tips\/\">acknowledgments sections<\/a>; some restrict it entirely<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td><strong>Verify data-handling\/privacy terms<\/strong> of the specific AI tool (e.g., is input used for model training? Is it enterprise\/HIPAA-eligible?)<\/td>\n<td>Consumer-facing AI tools often are not appropriate for even de-identified sensitive health data unless covered by a BAA or equivalent<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td><strong>Compile and organize the source clinical record first<\/strong> (labs, imaging reports, timeline, treatment course) into a clean document<\/td>\n<td>Gives the AI accurate grounding material and reduces the temptation for it to \u201cfill gaps\u201d<\/td>\n<\/tr>\n<tr>\n<td>6<\/td>\n<td><strong>Decide the reporting standard<\/strong> to follow (e.g., CARE guidelines) and have the checklist ready<\/td>\n<td>Ensures the AI draft is structured correctly from the outset rather than needing rework<\/td>\n<\/tr>\n<tr>\n<td>7<\/td>\n<td><strong>Define the <a href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-research-paper-tools-prompts-and-workflow-to-prevent-hallucination-and-sound-human\/\">AI\u2019s role in writing<\/a><\/strong> (formatting\/style help vs. content generation) and plan your fact-checking process<\/td>\n<td>Keeps the researcher (not the AI tool) responsible for clinical accuracy and reasoning<\/td>\n<\/tr>\n<tr>\n<td>8<\/td>\n<td><strong>Confirm authorship rules<\/strong> with co-authors and preferred journals (AI cannot be listed as an author under ICMJE criteria)<\/td>\n<td>Avoids <a href=\"https:\/\/www.editage.com\/blog\/first-author-vs-corresponding-author-in-a-research-paper-how-to-decide-authorship-with-examples-templates\/\">authorship disputes<\/a> or journal rejection for policy violations<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>A general note, since this sits close to real patient care: whatever tool is used, the researcher (not the AI tool) remains fully responsible for verifying every clinical fact, date, and value against the source record before submission. AI-assisted drafts should be treated as unverified until checked line-by-line.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Strong_vs_Weak_Prompts_for_AI-Drafted_Case_Reports\"><\/span>Strong vs. Weak Prompts for AI-Drafted Case Reports<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<table>\n<thead>\n<tr>\n<td><\/td>\n<td><strong>Weak Prompt<\/strong><\/td>\n<td><strong>Why It\u2019s Weak<\/strong><\/td>\n<td><strong>Strong Prompt<\/strong><\/td>\n<td><strong>Why It\u2019s Stronger<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>1<\/td>\n<td>\u201cWrite a case report about a patient with lupus nephritis.\u201d<\/td>\n<td>No patient specifics, no structure, invites fabrication of clinical details<\/td>\n<td>\u201cUsing the attached de-identified clinical timeline (labs, biopsy report, treatment course), draft a case report following the CARE guidelines structure (Title, Abstract, Introduction, Case Presentation, Discussion, Conclusion). Do not add any clinical detail not present in the source material.\u201d<\/td>\n<td>Grounds the AI in real, supplied data; specifies a recognized reporting standard; explicitly forbids invention<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td>\u201cMake it sound more professional\/academic.\u201d<\/td>\n<td>Vague stylistic request with no control over factual content<\/td>\n<td>\u201cRevise the tone to match journal X\u2019s style guide (attached), keeping every clinical fact, date, and lab value exactly as in my draft. Flag any sentence where you had to infer or generalize instead of using stated data.\u201d<\/td>\n<td>Separates style editing from content generation; asks AI to self-report uncertain inferences<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td>\u201cSummarize the patient\u2019s history for the case report.\u201d<\/td>\n<td>AI may compress\/omit clinically significant negatives or timeline order<\/td>\n<td>\u201cSummarize only the events in this timeline (attached) in chronological order, preserving all dates, dosages, and lab values verbatim. Do not interpret significance or add causal language.\u201d<\/td>\n<td>Constrains to extraction\/reformatting, not clinical interpretation<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td>\u201cWhat\u2019s the likely diagnosis\/discussion points for this case?\u201d<\/td>\n<td>Asks AI to perform clinical reasoning it isn\u2019t licensed or reliable to do<\/td>\n<td>\u201cGiven the discussion points I\u2019ve already drafted (attached), check for internal consistency and suggest 2\u20133 relevant differential diagnoses to prompt my own literature review \u2014 do not state a diagnosis as fact.\u201d<\/td>\n<td>Keeps clinical judgment with the researcher; uses AI as a checklist\/prompt generator, not decision-maker<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td>\u201cFind similar published cases and cite them.\u201d<\/td>\n<td>High risk of fabricated or mismatched citations<\/td>\n<td>\u201cList search terms and databases (PubMed, Embase) I should use to find comparable published cases. Do not generate citations yourself.\u201d<\/td>\n<td>Avoids <a href=\"https:\/\/www.editage.com\/blog\/how-to-check-for-hallucinations-in-ai-text-examples-and-checklist-for-researchers-and-students\/\">AI hallucination<\/a> of references entirely<\/td>\n<\/tr>\n<tr>\n<td>6<\/td>\n<td>\u201cFill in the patient\u2019s demographics\/history if I didn\u2019t include them.\u201d<\/td>\n<td>Actively invites fabrication of PHI-adjacent or clinical facts<\/td>\n<td>\u201cIdentify any sections where information is missing or ambiguous in my draft, and list them as open questions for me to fill in \u2014 do not generate placeholder content.\u201d<\/td>\n<td>Makes gaps visible instead of silently inventing data<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Here\u2019s a new section you can slot in \u2014 likely after \u201cA Practical Division of Labor\u201d and before \u201cThe Ethics of Uploading Patient Data\u201d:<\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_to_Avoid_Hallucinations_When_Using_AI_to_Write_a_Case_Report\"><\/span>How to Avoid Hallucinations When Using AI to Write a Case Report<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Hallucination in a case report is particularly dangerous because it doesn\u2019t look like an error \u2014 a fabricated lab value or a misremembered drug dose reads exactly as fluently as a real one. The following practices reduce the risk substantially.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Before_drafting\"><\/span>Before drafting<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Give the AI tool the complete source material (notes, lab values, imaging reports) rather than asking it to \u201cwrite up a case of biliary atresia\u201d from general knowledge. Hallucination risk rises sharply whenever the model is filling gaps instead of transcribing.<\/li>\n<li>Avoid asking the AI to generate specific numeric values, dates, or reference ranges from memory. If a normal range or a drug dosage needs to appear in the text, supply it yourself or verify it against a primary source rather than trusting the model\u2019s recall.<\/li>\n<li>Be wary of asking for citations. LLMs are well known for fabricating plausible-looking journal references (real author names attached to titles and page numbers that don\u2019t exist). Any citation an AI tool produces should be treated as a placeholder to verify, never as a finished reference.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"While_drafting\"><\/span>While drafting<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Read every clinical claim in the draft against the source notes line by line, not just for tone but for content. Check that every value, date, and finding traces back to something actually documented.<\/li>\n<li>Watch for the model \u201csmoothing over\u201d gaps in the notes. If the input said \u201clabs pending\u201d and the output says \u201clabs were within normal limits,\u201d that\u2019s a fabricated result, not a paraphrase.<\/li>\n<li>Be alert to invented specificity, for example, an AI draft turning \u201crecent surgery\u201d into \u201csurgery three weeks prior\u201d or \u201cmild anemia\u201d into \u201chemoglobin of 9.8 g\/dL\u201d when no such figure was given. Precise-sounding numbers are exactly where hallucination hides best, because they read as more credible than vague language.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"After_drafting\"><\/span>After drafting<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Run a dedicated fact-check pass separate from the language-and-flow edit. Treat checking claims against the source record as its own step, not something that happens automatically while reading for grammar.<\/li>\n<li>Verify every named drug, dose, guideline, and cited statistic independently, especially anything that wasn\u2019t explicitly present in the original clinical notes.<\/li>\n<li>If co-authors or the treating team are available, have them read the final draft specifically for factual accuracy before submission. A second clinician who was present for the case is often the fastest way to catch a subtly wrong detail that reads perfectly plausibly.<\/li>\n<\/ul>\n<p><strong>A general rule of thumb:<\/strong> the more fluent and specific an AI-generated sentence sounds, the more it deserves scrutiny rather than less. Hallucinated content is rarely vague or <a href=\"https:\/\/www.editage.com\/blog\/what-is-hedging-language-meaning-examples-and-importance\/\">hedged<\/a>. It tends to be confident and detailed, and this is precisely what makes it easy to miss on a quick read.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Ethics_of_Uploading_Patient_Data_into_AI_Tools\"><\/span><a name=\"_Toc235646531\"><\/a>The Ethics of Uploading Patient Data into AI Tools<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Before you can run to ChatGPT to upload your case notes, there is a prior question: What patient information is safe to give an AI tool at all? Pasting an unredacted clinical note into a general-purpose chatbot can constitute an unauthorized disclosure of protected health information, even if the model provider says it doesn\u2019t train on submitted data.<\/p>\n<p>The safer approach is de-identification before anything is entered into an AI tool. You need to remove names, exact dates, medical record numbers, specific institution, and any other detail that could identify the patient, either alone or combined with other case details, before inputting anything into an AI tool.<\/p>\n<p>Also, note that the usual patient consent form for publication doesn\u2019t automatically cover uploading the patient\u2019s records into a third-party AI system. It\u2019s best to get a clear sign-off from your hospital\u2019s data privacy team as well as IRB\/research ethics office before entering any patient\u2019s data into your own ChatGPT account or any other AI tool.<\/p>\n<p>These issues are not so pressing with the use of human editors as long as you choose reputed professional editing services with strong privacy and security systems. For example, Editage has ISO\/IEC 27001:2013\u2013certified IT security systems and all editors sign a rigorous confidentiality and non-disclosure agreement before they are assigned any client\u2019s manuscript or data.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Aligning_the_Case_Report_with_Journal_Requirements\"><\/span>Aligning the Case Report with Journal Requirements<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Many authors don\u2019t realize that there\u2019s no single, universally accepted format for a \u201ccase report\u201d. While the majority of journals expect an Introduction, Case Presentation, and Discussion, the exact section headings and requirements may differ. Let\u2019s take a look at some examples:<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Example_1_Blood\"><\/span>Example 1: <em>Blood<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><em>Blood<\/em> doesn\u2019t have a dedicated case report section, but will publish highly novel or important case reports as a <a href=\"https:\/\/ashpublications.org\/blood\/pages\/Article_Types\">Brief Report, Letter to Blood, or How I Treat article.<\/a> Each type comes with its own structure and word limits that an author must adhere to.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Example_2_BMJ_Case_Reports\"><\/span>Example 2: <em>BMJ Case Reports<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><em>BMJ Case Reports<\/em> publishes multiple types of case reports, not just the conventional ones. The journal asks authors to directly download and input text into their templates, which contain unique structural and content requirements. For example, the <a href=\"https:\/\/casereports.bmj.com\/pages\/authors#Case_report_templates\">2026 template for a Clinical Case Report<\/a> has dedicated sections for Differential Diagnosis, Outcome and Follow-Up, and Patient\u2019s Perspective, which require much more detail than what a typical case report provides.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Example_3_European_Heart_Journal_%E2%80%93_Case_Reports\"><\/span>Example 3: <em>European Heart Journal &#8211; Case Reports<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><em><a href=\"https:\/\/academic.oup.com\/ehjcr\/pages\/General_Instructions#Reporting%20Guidelines\">European Heart Journal Case Reports<\/a><\/em> requires a special summary figure to be placed after the Introduction, and this figure should illustrate the key teaching points of the case for clinicians. The journal also has a Grand Round section for cases where multiple specialties were involved in diagnosis, evaluation, and treatment. Word limits, number of references, and even number of authors permitted differ for each.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"The_Role_of_a_Medical_Editor_in_Case_Report_Formatting\"><\/span>The Role of a Medical Editor in Case Report Formatting<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Currently, LLMs can generate a case report in conventional sections, but once you shortlist a target journal, a professional editor can help you ensure that the case report is properly aligned with the journal\u2019s requirements.<\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_to_Avoid_Journal_Rejection_for_Using_AI\"><\/span>How to Avoid Journal Rejection for Using AI<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Journals aren\u2019t rejecting manuscripts because the authors used AI, and in fact, many journals now expect it and have framed specific policies around AI use (e.g., <em>JAMA<\/em>). What gets manuscripts rejected or sent back is mishandling the disclosure, the authorship question, no actual underlying contribution to knowledge, or the underlying data. The following practices reduce that risk.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Disclosure\"><\/span>Disclosure<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Check the specific target journal\u2019s instructions for authors before submitting. Policies differ in wording and placement (some want AI use noted in the methods, others in the cover letter or acknowledgments), and using the wrong format is a common, avoidable reason for desk rejection.<\/li>\n<li>State what the AI tool was used for, not just that one was used. \u201cAI was used to assist with language editing of the draft\u201d is a very different disclosure from \u201cAI was used to generate the first draft from clinical notes.\u201d<\/li>\n<li>Disclose every tool involved if more than one was used (for example, a drafting assistant and a separate grammar tool), rather than bundling them into a single generic statement.<\/li>\n<li>Don\u2019t skip disclosure because the AI\u2019s contribution feels minor. Editors increasingly screen for AI-generated text, and an undisclosed use that\u2019s later detected is treated as a transparency issue, not a language issue.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Authorship\"><\/span>Authorship<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Never list an AI tool as an author or co-author. Every major journal body has been explicit that AI cannot take responsibility for a manuscript\u2019s accuracy or integrity, which is a requirement of authorship, so an AI byline is an automatic rejection or a demand to correct it before review proceeds.<\/li>\n<li>Make sure a human author has personally verified every clinical fact, reference, and figure in the manuscript, since responsibility for accuracy sits entirely with the named human authors regardless of what tool helped produce the sentence.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Content_and_originality\"><\/span>Content and originality<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>A professional editor can make sure that the novelty and teaching value of the case are highlighted appropriately. Reviewers are quick to reject case reports that read as generic, and a disclosure statement won\u2019t rescue a paper whose \u201cwhy this case matters\u201d argument is thin or reads like AI-boilerplate.<\/li>\n<li>Run the near-final draft through a plagiarism or text-similarity checker before submission. AI tools can reproduce phrasing that is closer to existing published case reports than authors expect, which some journals flag independently of AI disclosure.<\/li>\n<li>Avoid submitting a manuscript that reads as obviously AI-generated in tone throughout (repetitive sentence structures, generic hedging phrases, overly uniform paragraph lengths). Beyond the ethics of disclosure, this is now something reviewers notice and comment on unprompted, and it can color how carefully they scrutinize the rest of the submission. Professional editing is invaluable in cutting out wordy AI-boilerplate text and in flagging places where beautiful prose masks the fact that there\u2019s actually nothing substantial said.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Data_and_consent\"><\/span>Data and consent<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Confirm that any patient data used to prompt an AI tool during drafting was properly de-identified beforehand, and be prepared to state this if asked. Your journal may request confirmation that no identifiable patient data was entered into a third-party AI system.<\/li>\n<li>Keep the patient consent-for-publication paperwork and any AI-use disclosure as separate items.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_Line\"><\/span><a name=\"_Toc235646532\"><\/a>Bottom Line<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>AI is a genuinely useful first-pass writer for case reports: it is fast, it produces grammatically sound prose, and it can save a clinician hours of drafting time. But what actually gets a case report published is novelty and teaching value. LLMs cannot tell you whether the reasoning holds up, whether the terminology is precise, and whether the novelty and teaching value can convince a journal editor or peer reviewer that the case is worth publishing. Pairing an AI draft with your own check for accuracy and finally a human review from a subject-matter expert is the combination that is most likely to produce a case report that gets published.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span>Frequently Asked Questions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"Do_I_need_to_disclose_that_I_used_AI_like_ChatGPT_to_write_my_case_report\"><\/span>Do I need to disclose that I used AI (like ChatGPT) to write my case report?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Yes, in almost all cases. Most major journals now follow ICMJE or COPE-aligned policies requiring <a href=\"https:\/\/www.editage.com\/blog\/how-to-write-an-ai-disclosure-statement-examples-and-format-for-journal-articles-and-dissertations\/\">disclosure of AI tool use<\/a> in the Methods, Acknowledgments, or a dedicated \u201cAI Use\u201d statement. Typically you need to name the tool, version, and what it was used for (e.g., \u201cdrafting,\u201d \u201clanguage editing\u201d). Check your target journal\u2019s specific author guidelines, as wording requirements vary.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Can_ChatGPT_or_another_AI_be_listed_as_a_co-author_on_a_case_report\"><\/span>Can ChatGPT or another AI be listed as a co-author on a case report?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>No. ICMJE authorship criteria require accountability for the work, which AI tools cannot hold. Nearly all publishers (Elsevier, Springer, JAMA, NEJM, etc.) explicitly prohibit listing AI as an author, though it can be credited in acknowledgments or a disclosure statement.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Will_journals_reject_a_case_report_because_it_was_drafted_with_AI\"><\/span>Will journals reject a case report because it was drafted with AI?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Most journals accept AI-assisted drafting if properly disclosed and if the content is verified and substantially reviewed by human authors. Rejection risk comes from non-disclosure, fabricated citations or facts, or a paper that reads as generic\/templated.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Is_using_AI_to_write_a_medical_case_report_considered_plagiarism\"><\/span>Is using AI to write a medical case report considered plagiarism?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Not inherently, but it can create plagiarism-adjacent risks: AI models may reproduce phrasing close to existing published text without attribution, or \u201cself-plagiarize\u201d boilerplate phrasing across many drafts. Running the final draft through a plagiarism checker (e.g., iThenticate, which many journals use themselves) before submission is standard practice.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"How_do_I_cite_or_reference_an_AI_tool_like_ChatGPT_in_a_case_report\"><\/span>How do I cite or reference an AI tool like ChatGPT in a case report?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Most style guides (e.g., AMA, APA 7th edition) now have specific formats for <a href=\"https:\/\/www.editage.com\/blog\/how-to-cite-generative-ai-in-academic-writing-apa-mla-chicago-ieee-turabian-and-ama\/\">citing AI interactions<\/a>. This could be in a footnote, as a personal communication, or an entry in the reference list that includes the prompt as well as a shareable link of the entire AI conversation. But note that AI output itself is considered a weak source, owing to the risk of hallucinations, and hence it\u2019s much better to cite real, published journal articles, books, reports, posters, etc.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"How_much_of_a_case_report_can_be_AI-generated_before_its_a_problem\"><\/span>How much of a case report can be AI-generated before it\u2019s a problem?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>There\u2019s no universal percentage threshold \u2014 the issue is verification, not volume. Journals generally distinguish between AI helping with language\/structure\/formatting (broadly acceptable with disclosure) versus AI generating clinical content, citations, or discussion points without human verification (high-risk and can lead to retraction if factual errors or fabricated references slip through).<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Can_AI-generated_case_reports_contain_fake_or_%E2%80%9Challucinated%E2%80%9D_citations\"><\/span>Can AI-generated case reports contain fake or \u201challucinated\u201d citations?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Yes, this is one of the most common and serious risks. AI language models can generate plausible-looking but nonexistent references or misattribute real findings to the wrong study. Every citation in an AI-assisted draft must be manually verified against the original source (e.g., PubMed) before submission; never trust AI-generated reference lists as-is.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Do_I_need_patient_consent_if_I_use_AI_to_help_write_their_case_report\"><\/span>Do I need patient consent if I use AI to help write their case report?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Patient consent for publication is required regardless of whether AI is used, but there\u2019s an added consideration: de-identified patient data should not be entered into non-HIPAA-compliant or public AI tools, as this could violate patient privacy protections even after consent is obtained for the eventual publication. Always get confirmation from your institute\u2019s IRB before entering any patient data into an AI tool.<\/p>\n","protected":false},"excerpt":{"rendered":"Highlights: AI tools, especially large language models (LLMs), can speed up drafting a case report. They are not able to effectively spot logical flaws, unclear novelty or weak implications for practice. A human editor can improve flow, coherence, and technical word choice in an AI-generated manuscript. An optimum workflow for busy clinicians is to use [&hellip;]","protected":false},"author":3,"featured_media":1658,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_ayudawp_aiss_exclude":false,"_ayudawp_aiss_summary":"Format, Tips, Examples This article explains what AI genuinely handles well when drafting a case report, where a human pass adds real value, how to avoid AI hallucinations in your case report, and the ethics of putting patient information into an AI tool in the first place. For example, the 2026 template for a Clinical Case Report has dedicated sections for Differential Diagnosis, Outcome and Follow-Up, and Patient\u2019s Perspective, which require much more detail than what a typical case report provides. &nbsp;. Currently, LLMs can generate a case report in conventional sections, but once you shortlist a target journal, a professional editor can help you ensure that the case report is properly aligned with the journal\u2019s requirements. &nbsp;.","_ayudawp_aiss_summary_provider":"manual","_ayudawp_aiss_summary_hash":"bd29183ce4c679f95fe1541b9394b1aa70d2aad5"},"categories":[4],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to Use AI to Write a Case Report: Prompts, Examples, and Tips to Avoid Hallucinations - Educational Articles For Researchers, Students And Authors - Editage Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.editage.com\/blog\/how-to-use-ai-to-write-a-case-report-prompts-examples-and-tips-to-avoid-hallucinations\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to Use AI to Write a Case Report: Prompts, Examples, and Tips to Avoid Hallucinations - Educational Articles For Researchers, Students And Authors - Editage Blog\" \/>\n<meta property=\"og:description\" content=\"Highlights: AI tools, especially large language models (LLMs), can speed up drafting a case report. 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