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The paper reviews evidence from systematic reviews showing frequent misuse of key terms, especially “prediction,” often applied to association findings or retrospective analyses. It clarifies appropriate usage of prediction and recommends “prospective prediction,” details validation procedures for generalizable models, discusses overfitting and generalization, and explains relationships among features, predictors, risk factors, and causal factors.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/ai-and-machine-learning-terminology-in-medicine-psychology-and-social-sciences-tutorial-and-practical-recommendations/290649/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/ai-and-machine-learning-terminology-in-medicine-psychology-and-social-sciences-tutorial-and-practical-recommendations/290649.png","ImageObject",300,407,{"name":92,"@type":93},"Theodore","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-17",true,{"@type":101,"interactionType":102,"userInteractionCount":4},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"Why does the paper say terminological confusion is increasing in these fields?","Question",{"text":111,"@type":112},"Rapid growth of AI and ML in medicine, psychology, and social sciences has led to terminology being applied inconsistently and imprecisely, creating confusion for researchers, clinicians, and policymakers.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"What is the main concern about the term “prediction”?",{"text":116,"@type":112},"“Prediction” is often misused to describe association results or retrospective analyses, leading to inflated expectations about what models can actually do.",{"name":118,"@type":109,"acceptedAnswer":119},"What recommendations does the paper emphasize for clearer terminology use?",{"text":120,"@type":112},"It clarifies when “prediction” should be used, recommends using “prospective prediction” for future prediction, and describes essential validation procedures for model generalizability.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},290649,1789642269,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":4,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":138,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":128,"read_time":143},7971461740886,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","| JOURNAL OF MEDICAL INTERNET RESEARCH Cao et al\u003Cbr>Tutorial\u003Cbr>AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |\n| --- |\n|  |\n| Bo Cao 1,2,3 , PhD; Russell Greiner1,2,4 , PhD; Andrew Greenshaw 1 , PhD; Jie Sui5 , PhD |\n| 1Department of Psychiatry, University of Alberta, Edmonton, AB, Canada\u003Cbr>2Department of Computing Science, Faculty of Science, University of Alberta, Edmonton, AB, Canada 3School of Public Health, University of Alberta, Edmonton, AB, Canada\u003Cbr>4Alberta Machine Intelligence Institute (Amii), Edmonton, AB, Canada 5School of Psychology, University of Aberdeen, Aberdeen, United Kingdom\u003Cbr>Corresponding Author:\u003Cbr>Bo Cao, PhD Department of Psychiatry University of Alberta\u003Cbr>4-142A Katz Group Centre for Research, 11315-87 Ave NW Edmonton, AB T6G 2B7\u003Cbr>Canada\u003Cbr>Phone: 1 7804929576\u003Cbr>Email: [cloudbocao@gmail.com](cloudbocao@gmail.com)\u003Cbr>Abstract |\n| Recent applications of artificial intelligence (AI) and machine learning in medicine, psychology, and social sciences have led to common terminological confusions. In this paper, we review emerging evidence from systematic reviews documenting widespread misuse of key terms, particularly “prediction” being applied to studies merely demonstrating association or retrospective analysis. We clarify when “prediction” should be used and recommend using “prospective prediction” for future prediction; explain validation procedures essential for model generalizability; discuss overfitting and generalization in machine learning and traditional regression methods; clarify relationships between features, independent variables, predictors, risk factors, and causal factors; and clarify the hierarchical relationship between AI, machine learning, deep learning, large language models, and generative AI. We provide evidence-based recommendations for terminology use that can facilitate clearer communication among researchers from different disciplines and between the research community and the public, ultimately advancing the rigorous application of AI in medicine, psychology, and social sciences.\u003Cbr>J Med Internet Res 2025;27:e66100; doi:  10.2196/66100 |\n\nKeywords: artificial intelligence; machine learning; terminology; medicine; psychology; social sciences; prediction; regression; deep learning; tutorial; prospective prediction; validation  \nChallenges  \nThe rapid growth of artificial intelligence (AI) and machine learning (ML) in medicine, psychology, and social sciences has led to a proliferation of terminology that is often inconsistently and imprecisely applied [1,2] . This inconsistency creates confusion for researchers, clinicians, and policymakers who need to interpret and apply these technologies. Perhaps the most notable example of terminological confusion in the field involves the concept of “prediction,”which is frequently misused in the literature [3,4] . However, similar confusion extends to other key terms such as  \n“validation,” “features,” and even the distinctions between AI, ML, and deep learning (DL) [1] .  \nThe confusion about “prediction” is particularly widespread and merits special attention. Yarkoni and Westfall [5] have argued that psychology’s emphasis on explaining the causes of behavior rather than predicting future behavior has led to research programs that provide intricate theories but have little ability to predict future behaviors with appreciable accuracy. McCall et al [4] highlight this issue in the context of sports science and medicine, noting that much of the confusion stems from a mismatch between statistical modeling and subsequent interpretation of findings. After  \n[https://www.jmir.org/2025/1/e66100](https://www.jmir.org/2025/1/e66100) J Med Internet Res 2025 | vol. 27 | e66100 | p. 1  \n(page number not for citation purposes)  \nJOURNAL OF MEDICAL INTERNET RESEARCH Cao et al  \nexamining the literature in sports science that claimed to predict performance, talent, or inj","cbCaieoPUSUUEsUN","https://ap.wps.com/l/cbCaieoPUSUUEsUN","pdf",2420911,13,"English","# Abstract\n# Challenges\n## Terminological confusion around “prediction”\n## Validation and prospective use\n## Generalizability and study design","[{\"question\":\"Why does the paper say terminological confusion is increasing in these fields?\",\"answer\":\"Rapid growth of AI and ML in medicine, psychology, and social sciences has led to terminology being applied inconsistently and imprecisely, creating confusion for researchers, clinicians, and policymakers.\"},{\"question\":\"What is the main concern about the term “prediction”?\",\"answer\":\"“Prediction” is often misused to describe association results or retrospective analyses, leading to inflated expectations about what models can actually do.\"},{\"question\":\"What recommendations does the paper emphasize for clearer terminology use?\",\"answer\":\"It clarifies when “prediction” should be used, recommends using “prospective prediction” for future prediction, and describes essential validation procedures for model generalizability.\"}]","AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences - Tutorial and Practical Recommendations | PDF",33]