[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119148-en":3,"doc-seo-119148-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119148,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine Learning and Health Science Research - Tutorial","Machine learning (ML) has expanded rapidly in health science research because it can manage complex, high-dimensional data and support multiple analytical goals. A structured guideline is provided to help health science researchers understand ML’s strengths and limitations, integrate ML into study workflows, and move from research question formulation to study design and appropriate analysis techniques for specialized data types. The framework is intended to improve clarity, planning, and reproducibility across ML-based investigations.","JOURNAL OF MEDICAL INTERNET RESEARCH Cho et al  \nTutorial  \nMachine Learning and Health Science Research: Tutorial  \n\n| Hunyong Cho 1*, PhD; Jane She 1*, BA; Daniel De Marchi1, BSc; Helal El-Zaatari1, BSc; Edward L Barnes2,3, MPH, MD; Anna R Kahkoska4,5,6, MD, PhD; Michael R Kosorok 1, MM, PhD; Arti V Virkud7, PhD |\n| --- |\n| 1Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States\u003Cbr>2Division of Gastroenterology and Hepatology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States 3Center for Gastrointestinal Biology and Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States 4Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States\u003Cbr>5Division of Endocrinology and Metabolism, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States 6Center for Aging and Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States\u003Cbr>7Kidney Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States\u003Cbr>*these authors contributed equally\u003Cbr>Corresponding Author:\u003Cbr>Jane She, BA\u003Cbr>Department of Biostatistics\u003Cbr>University of North Carolina at Chapel Hill 3101 McGavran-Greenberg Hall\u003Cbr>CB \\#7420\u003Cbr>Chapel Hill, NC, 27599-7420 United States\u003Cbr>Phone: 1 (919) 966 7250\u003Cbr>Email: [jane.she@unc.edu](jane.she@unc.edu)\u003Cbr>Abstract |\n| Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health science researchers in understanding the strengths and limitations ofML and to facilitate its integration into their studies, we present here a guideline for integrating ML into an analysis through a structured framework, covering steps from framing a research question to study design and analysis techniques for specialized data types.\u003Cbr>(J Med Internet Res 2024;26:e50890) doi:  10.2196/50890 |\n\nKEYWORDS  \nhealth science researcher; machine learning pipeline; machine learning; medical machine learning; precision medicine; reproducibility; unsupervised learning  \nIntroduction  \nAs a brief overview, machine learning (ML) is generally characterized by model complexity and capacity for processing high-dimensional or complicated data forms and is often mentioned as an antonym to traditional statistical learning algorithms. However, this division is not clear, and ML algorithms range from traditional statistical analysis tools such as simple linear regression to cutting-edge deep neural network algorithms. While often used interchangeably with artificial intelligence (AI), ML is a subset of AI and seeks to use data-driven methods to identify patterns and make decisions. This can then be used in the field ofAI to allow problem-solving and decision-making.  \nML is becoming increasingly popular in the research community due to the proliferation of complex or unstructured data sets and the increased capacity and access to computing power needed to run these models. ML models can often discover sophisticated and surprising patterns in these data sets that would be difficult to discover using classical methods [1,2] . The health science research domain has been no exception to this paradigm, as the health science fields have an abundance of data well suited for these models, such as genomics sequencing data and electronic health records (EHR) data [3-6]. Applications ofML to the health field can lead to targeted interventions to provide support for health care professionals [7] . ML has also become almost indispensable to the fast-growing field of PM, which  \n[https://www.jmir.org/2024/1/e50890](https://www.jmir.org/2024/1/e50890)  \nXSL• FO  \nRenderX  \nJ Med Internet Res 2024 | vol. 26 | e50890 | p. 1 (page number not for citation purposes)  \nuses rich patient information to pre","cbCaidMfYyIsNDnH","https://ap.wps.com/l/cbCaidMfYyIsNDnH","pdf",522357,1,15,"English","en",105,"# Introduction\n## Experimentation\n### Refining Research Questions: What Can Machine Learning Do?\n### ML methods for prediction, estimation, causal understanding, and decision support","[{\"question\":\"How does machine learning support health science research tasks?\",\"answer\":\"Machine learning can be used for prediction, estimation, understanding causal associations, and decision support, and it can also support main analyses in health studies.\"},{\"question\":\"Why is ML integration in study design emphasized in the tutorial?\",\"answer\":\"The tutorial provides a structured framework to move from framing research questions to study design and selecting analysis techniques for specialized data types, while emphasizing documentation and preplanning for reproducibility.\"},{\"question\":\"What kinds of data and applications are discussed as drivers for ML adoption?\",\"answer\":\"The text highlights complex and unstructured datasets, including genomics sequencing data and electronic health records, and notes applications such as targeted interventions and precision medicine using rich patient information.\"}]","Machine Learning and Health Science Research - Tutorial | PDF",1785722734,38,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"machine-learning-and-health-science-research-tutorial","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-and-health-science-research-tutorial/119148/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"How does machine learning support health science research tasks?","Question",{"text":76,"@type":77},"Machine learning can be used for prediction, estimation, understanding causal associations, and decision support, and it can also support main analyses in health studies.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Why is ML integration in study design emphasized in the tutorial?",{"text":81,"@type":77},"The tutorial provides a structured framework to move from framing research questions to study design and selecting analysis techniques for specialized data types, while emphasizing documentation and preplanning for reproducibility.",{"name":83,"@type":74,"acceptedAnswer":84},"What kinds of data and applications are discussed as drivers for ML adoption?",{"text":85,"@type":77},"The text highlights complex and unstructured datasets, including genomics sequencing data and electronic health records, and notes applications such as targeted interventions and precision medicine using rich patient information.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]