{"id":704,"date":"2023-11-01T13:53:06","date_gmt":"2023-11-01T13:53:06","guid":{"rendered":"https:\/\/www.editage.com\/blog\/?p=704"},"modified":"2023-11-01T13:53:44","modified_gmt":"2023-11-01T13:53:44","slug":"random-forests-for-big-biomedical-data","status":"publish","type":"post","link":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/","title":{"rendered":"A Handy Guide to Random Forests for Big Biomedical Data"},"content":{"rendered":"\n<p>In today\u2019s rapidly advancing world of biomedical research, the amount of data generated is staggering. From&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/statistical-methods-in-genetics-research\/\" target=\"_blank\" rel=\"noreferrer noopener\">genomics<\/a> to&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/best-practices-in-retrospective-chart-reviews-for-biomedical-researchers\/\" target=\"_blank\" rel=\"noreferrer noopener\">clinical records<\/a>, the volume of information can be overwhelming. Fortunately, there\u2019s a powerful tool at our disposal \u2013 Random Forests. In this blog post, we\u2019ll explore how you can use Random Forests to analyze&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/does-big-data-mean-good-data-5-challenges-researchers-face-while-handling-big-data-sets?refer=insights-search-posts\" target=\"_blank\" rel=\"noreferrer noopener\">big biomedical data<\/a> and unlock valuable insights that can drive your research forward.<\/p>\n\n\n\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\/random-forests-for-big-biomedical-data\/#What_Are_Random_Forests\" >What Are Random Forests?<\/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\/random-forests-for-big-biomedical-data\/#Why_Random_Forests_for_Biomedical_Data\" >Why Random Forests for Biomedical Data?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#Getting_Started_with_Random_Forests\" >Getting Started with Random Forests<\/a><\/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\/random-forests-for-big-biomedical-data\/#Practical_Applications_of_Random_Forests_in_Biomedicine\" >Practical Applications of Random Forests in Biomedicine<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"What_Are_Random_Forests\"><\/span><strong>What Are Random Forests?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Let\u2019s start with the basics. They are a&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/harnessing-machine-learning-for-advanced-data-analysis\/\" rel=\"noreferrer noopener\" target=\"_blank\">machine learning<\/a> algorithm used for both classification and regression tasks. In a Random Forest, a collection of decision trees is created, each trained on a different subset of the data with some randomness introduced during the tree-building process. These individual trees then &#8220;vote&#8221; on the outcome (in classification) or contribute predictions (in&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/what-is-regression-and-types-of-regression-for-biomedical-researchers\/\" rel=\"noreferrer noopener\" target=\"_blank\">regression<\/a>), and the final result is a combination of these contributions. This ensemble approach often results in more robust and accurate predictions compared to using a single decision tree.<\/p>\n\n\n\n<p>Random Forests belong to the family of ensemble learning methods, where multiple models (decision trees in the case of Random Forests) are combined to improve predictive accuracy and reduce overfitting (i.e., where the model learns the training data so well that it can\u2019t generalize to any other data).<\/p>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Why_Random_Forests_for_Biomedical_Data\"><\/span><strong>Why Random Forests for Biomedical Data?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Let\u2019s look at the main reasons random forests are becoming increasingly popular in biomedical research:<\/p>\n\n\n\n<ol><li>Handles High Dimensionality: Biomedical data often comes with numerous features (genes, proteins, clinical parameters). Random Forests can deal with&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/high-dimensional-data-in-biomedical-research\/\" target=\"_blank\" rel=\"noreferrer noopener\">high-dimensional data<\/a> effortlessly.<\/li><li>Tackles Imbalanced Data: In many biomedical studies, you encounter imbalanced datasets, where one class greatly outnumbers the other (e.g., rare diseases). Random Forests can handle such situations gracefully.<\/li><li>Feature Importance: Random Forests help identify the most important features contributing to your analysis, aiding in feature selection and interpretation.<\/li><li>Non-linearity: Random Forests can capture complex, non-linear&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/differences-between-correlation-and-regression-learn-about-different-types-of-statistical-relationships?refer=insights-search-posts\" target=\"_blank\" rel=\"noreferrer noopener\">relationships<\/a> in your data, which is common in biology and medicine.<\/li><\/ol>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Getting_Started_with_Random_Forests\"><\/span><strong>Getting Started with Random Forests<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Here\u2019s a step-by-step guide to using Random Forests to analyze big biomedical data:<\/p>\n\n\n\n<p>1. Data Preprocessing<\/p>\n\n\n\n<ul><li>Begin by&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/data-cleaning-strategies-for-large-scale-biomedical-datasets-challenges-and-solutions?refer=insights-search-posts\" rel=\"noreferrer noopener\" target=\"_blank\">cleaning your data<\/a> \u2013 remove&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/statistical-solutions-to-overcome-missing-data-in-clinical-trials-and-observational-studies?refer=insights-search-posts\" rel=\"noreferrer noopener\" target=\"_blank\">missing<\/a> values,&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/taming-outliers-in-biomedical-research-a-handy-guide?refer=insights-search-posts\" rel=\"noreferrer noopener\" target=\"_blank\">outliers<\/a>, and irrelevant features.<\/li><li>Split your data into a training set and a testing set (usually 70\/30 or 80\/20).<\/li><li>Encode categorical variables (e.g., one-hot encoding) if needed.<\/li><\/ul>\n\n\n\n<p>2. Train Your Forest<\/p>\n\n\n\n<ul><li>Choose the number of trees (generally more is better, but watch for overfitting).<\/li><li>Train the Random Forest on your training data. The forest will learn the underlying patterns in your data.<\/li><\/ul>\n\n\n\n<p>3. Evaluate Your Model<\/p>\n\n\n\n<ul><li>Use your testing data to assess the performance of your Random Forest. Common metrics include accuracy, precision, recall, and F1-score.<\/li><li>Visualize the feature importance to understand which variables are driving the predictions.<\/li><\/ul>\n\n\n\n<p>4. Tune Your Model<\/p>\n\n\n\n<ul><li>If your model isn\u2019t performing as desired, try adjusting hyperparameters like the number of trees or maximum depth.<\/li><li><a href=\"https:\/\/www.editage.com\/insights\/cross-validation-an-essential-tool-for-biomedical-researchers?refer=insights-search-posts\" rel=\"noreferrer noopener\" target=\"_blank\">Cross-validation<\/a> can help fine-tune your model and prevent overfitting.<\/li><\/ul>\n\n\n\n<p>5. Interpret the Results<\/p>\n\n\n\n<ul><li>Random Forests provide feature importance scores. Use these to gain insights into which variables are crucial for your analysis.<\/li><li>Visualizations such as partial dependence plots can help you understand the relationship between specific variables and the target outcome.<\/li><\/ul>\n\n\n\n<h2><span class=\"ez-toc-section\" id=\"Practical_Applications_of_Random_Forests_in_Biomedicine\"><\/span><strong>Practical Applications of Random Forests in Biomedicine<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Random Forests have found extensive applications in biomedical research:<\/p>\n\n\n\n<ul><li>Disease Prediction: They can predict disease outcomes based on genetic, clinical, or&nbsp;<a href=\"https:\/\/www.editage.com\/blog\/dimension-reduction-technique-omics-data\/\" target=\"_blank\" rel=\"noreferrer noopener\">omics<\/a> data. For instance, see how Velazquez et al. (2021) used Random Forests to predict conversion of early mild cognitive impairment to Alzheimer\u2019s disease.<\/li><li>Drug Discovery: Identifying potential drug candidates by analyzing molecular features. For example,&nbsp;<a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/31295321\/\" target=\"_blank\" rel=\"noreferrer noopener\">Lind and Anderson (2019)<\/a> used Random Forests to predict drug activity against cancer cells, to enable personalized oncology medicine.<\/li><li>Biological Marker Discovery: Identifying&nbsp;<a href=\"https:\/\/www.editage.com\/insights\/identifying-biomarkers-from-omics-data-the-role-of-statistics?refer=insights-search-posts\" target=\"_blank\" rel=\"noreferrer noopener\">biomarkers<\/a> for diseases or conditions. Take a look at&nbsp;<a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/33228632\/\" target=\"_blank\" rel=\"noreferrer noopener\">Acharjee et al.\u2019s (2020)<\/a> Random Forests-based framework for biomarker discovery.<\/li><li>Image Analysis: Analyzing medical images like X-rays and MRI scans for diagnosis. See how&nbsp;<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC7071377\/\" target=\"_blank\" rel=\"noreferrer noopener\">Kamarajan et al. (2020)<\/a> used Random Forests to analyze fMRI data in individuals with alcohol use disorder.<\/li><\/ul>\n\n\n\n<p><strong>Conclusion<\/strong><\/p>\n\n\n\n<p>Big biomedical data is a treasure trove of information waiting to be unlocked. Random Forests offer a robust and versatile tool for researchers working with big data. With the ability to handle high-dimensional data and imbalanced datasets, Random Forests can help you make sense of complex biological systems.<\/p>\n\n\n\n<p><em>Want to know more about using machine learning in data analysis? Take help from an expert biostatistician under&nbsp;Editage\u2019s&nbsp;<\/em><a href=\"https:\/\/www.editage.com\/services\/publishing-services-packs\/statistical-analysis\" rel=\"noreferrer noopener\" target=\"_blank\"><em>Statistical Analysis &amp; Review Services<\/em><\/a><em>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"In today\u2019s rapidly advancing world of biomedical research, the amount of data generated is staggering. From&nbsp;genomics to&nbsp;clinical records, the volume of information can be overwhelming. Fortunately, there\u2019s a powerful tool at our disposal \u2013 Random Forests. In this blog post, we\u2019ll explore how you can use Random Forests to analyze&nbsp;big biomedical data and unlock valuable [&hellip;]","protected":false},"author":2,"featured_media":705,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_ayudawp_aiss_exclude":false,"_ayudawp_aiss_summary":"","_ayudawp_aiss_summary_provider":"","_ayudawp_aiss_summary_hash":""},"categories":[14],"tags":[23,24],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>A Handy Guide to Random Forests for Big Biomedical Data | 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\/random-forests-for-big-biomedical-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Handy Guide to Random Forests for Big Biomedical Data | Editage Blog\" \/>\n<meta property=\"og:description\" content=\"In today\u2019s rapidly advancing world of biomedical research, the amount of data generated is staggering. From&nbsp;genomics to&nbsp;clinical records, the volume of information can be overwhelming. Fortunately, there\u2019s a powerful tool at our disposal \u2013 Random Forests. In this blog post, we\u2019ll explore how you can use Random Forests to analyze&nbsp;big biomedical data and unlock valuable [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\" \/>\n<meta property=\"og:site_name\" content=\"Educational Articles For Researchers, Students And Authors - Editage Blog\" \/>\n<meta property=\"article:published_time\" content=\"2023-11-01T13:53:06+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-01T13:53:44+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/www.editage.com\/blog\/wp-content\/uploads\/2023\/11\/random-forest-for-big-data.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"898\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Editor Editor\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Editor Editor\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\"},\"author\":{\"name\":\"Editor Editor\",\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/person\/194519c669bbbc38e9ed47cc02c5a44f\"},\"headline\":\"A Handy Guide to Random Forests for Big Biomedical Data\",\"datePublished\":\"2023-11-01T13:53:06+00:00\",\"dateModified\":\"2023-11-01T13:53:44+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\"},\"wordCount\":755,\"publisher\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#organization\"},\"keywords\":[\"Statistical Analysis Services\",\"Statistical Review Services\"],\"articleSection\":[\"Research Tips\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\",\"url\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\",\"name\":\"A Handy Guide to Random Forests for Big Biomedical Data | Editage Blog\",\"isPartOf\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#website\"},\"datePublished\":\"2023-11-01T13:53:06+00:00\",\"dateModified\":\"2023-11-01T13:53:44+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.editage.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"A Handy Guide to Random Forests for Big Biomedical Data\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.editage.com\/blog\/#website\",\"url\":\"https:\/\/www.editage.com\/blog\/\",\"name\":\"Educational Articles For Researchers, Students And Authors - Editage Blog\",\"description\":\"Get insightful educational articles from the world of academia for researchers, students and authors. Visit Editage Blog for helpful content and tips on getting published and writing articles that are up to international journal publication standards. Click here to find out more!\",\"publisher\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.editage.com\/blog\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.editage.com\/blog\/#organization\",\"name\":\"Educational Articles For Researchers, Students And Authors - Editage Blog\",\"url\":\"https:\/\/www.editage.com\/blog\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.editage.com\/blog\/wp-content\/uploads\/2022\/08\/editage-logo.png\",\"contentUrl\":\"https:\/\/www.editage.com\/blog\/wp-content\/uploads\/2022\/08\/editage-logo.png\",\"width\":394,\"height\":82,\"caption\":\"Educational Articles For Researchers, Students And Authors - Editage Blog\"},\"image\":{\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/logo\/image\/\"}},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/person\/194519c669bbbc38e9ed47cc02c5a44f\",\"name\":\"Editor Editor\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.editage.com\/blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/33094b932a69316d705f8302c2f84d82?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/33094b932a69316d705f8302c2f84d82?s=96&d=mm&r=g\",\"caption\":\"Editor Editor\"},\"url\":\"https:\/\/www.editage.com\/blog\/author\/admin-2\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"A Handy Guide to Random Forests for Big Biomedical Data | Editage Blog","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/","og_locale":"en_US","og_type":"article","og_title":"A Handy Guide to Random Forests for Big Biomedical Data | Editage Blog","og_description":"In today\u2019s rapidly advancing world of biomedical research, the amount of data generated is staggering. From&nbsp;genomics to&nbsp;clinical records, the volume of information can be overwhelming. Fortunately, there\u2019s a powerful tool at our disposal \u2013 Random Forests. In this blog post, we\u2019ll explore how you can use Random Forests to analyze&nbsp;big biomedical data and unlock valuable [&hellip;]","og_url":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/","og_site_name":"Educational Articles For Researchers, Students And Authors - Editage Blog","article_published_time":"2023-11-01T13:53:06+00:00","article_modified_time":"2023-11-01T13:53:44+00:00","og_image":[{"width":1792,"height":898,"url":"http:\/\/www.editage.com\/blog\/wp-content\/uploads\/2023\/11\/random-forest-for-big-data.jpg","type":"image\/jpeg"}],"author":"Editor Editor","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Editor Editor","Est. reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#article","isPartOf":{"@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/"},"author":{"name":"Editor Editor","@id":"https:\/\/www.editage.com\/blog\/#\/schema\/person\/194519c669bbbc38e9ed47cc02c5a44f"},"headline":"A Handy Guide to Random Forests for Big Biomedical Data","datePublished":"2023-11-01T13:53:06+00:00","dateModified":"2023-11-01T13:53:44+00:00","mainEntityOfPage":{"@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/"},"wordCount":755,"publisher":{"@id":"https:\/\/www.editage.com\/blog\/#organization"},"keywords":["Statistical Analysis Services","Statistical Review Services"],"articleSection":["Research Tips"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/","url":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/","name":"A Handy Guide to Random Forests for Big Biomedical Data | Editage Blog","isPartOf":{"@id":"https:\/\/www.editage.com\/blog\/#website"},"datePublished":"2023-11-01T13:53:06+00:00","dateModified":"2023-11-01T13:53:44+00:00","breadcrumb":{"@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.editage.com\/blog\/random-forests-for-big-biomedical-data\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.editage.com\/blog\/"},{"@type":"ListItem","position":2,"name":"A Handy Guide to Random Forests for Big Biomedical Data"}]},{"@type":"WebSite","@id":"https:\/\/www.editage.com\/blog\/#website","url":"https:\/\/www.editage.com\/blog\/","name":"Educational Articles For Researchers, Students And Authors - Editage Blog","description":"Get insightful educational articles from the world of academia for researchers, students and authors. Visit Editage Blog for helpful content and tips on getting published and writing articles that are up to international journal publication standards. Click here to find out more!","publisher":{"@id":"https:\/\/www.editage.com\/blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.editage.com\/blog\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.editage.com\/blog\/#organization","name":"Educational Articles For Researchers, Students And Authors - Editage Blog","url":"https:\/\/www.editage.com\/blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.editage.com\/blog\/#\/schema\/logo\/image\/","url":"https:\/\/www.editage.com\/blog\/wp-content\/uploads\/2022\/08\/editage-logo.png","contentUrl":"https:\/\/www.editage.com\/blog\/wp-content\/uploads\/2022\/08\/editage-logo.png","width":394,"height":82,"caption":"Educational Articles For Researchers, Students And Authors - Editage Blog"},"image":{"@id":"https:\/\/www.editage.com\/blog\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/www.editage.com\/blog\/#\/schema\/person\/194519c669bbbc38e9ed47cc02c5a44f","name":"Editor Editor","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.editage.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/33094b932a69316d705f8302c2f84d82?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/33094b932a69316d705f8302c2f84d82?s=96&d=mm&r=g","caption":"Editor Editor"},"url":"https:\/\/www.editage.com\/blog\/author\/admin-2\/"}]}},"jetpack_featured_media_url":"https:\/\/www.editage.com\/blog\/wp-content\/uploads\/2023\/11\/random-forest-for-big-data.jpg","_links":{"self":[{"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/posts\/704"}],"collection":[{"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/comments?post=704"}],"version-history":[{"count":2,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/posts\/704\/revisions"}],"predecessor-version":[{"id":707,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/posts\/704\/revisions\/707"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/media\/705"}],"wp:attachment":[{"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/media?parent=704"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/categories?post=704"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.editage.com\/blog\/wp-json\/wp\/v2\/tags?post=704"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}