AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations
AbstractRecent 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, partic...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2025-08-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e66100 |
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| _version_ | 1849223148796379136 |
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| author | Bo Cao Russell Greiner Andrew Greenshaw Jie Sui |
| author_facet | Bo Cao Russell Greiner Andrew Greenshaw Jie Sui |
| author_sort | Bo Cao |
| collection | DOAJ |
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AbstractRecent 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. |
| format | Article |
| id | doaj-art-28abef2518db4b70b618ffca8823ccd1 |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-28abef2518db4b70b618ffca8823ccd12025-08-25T21:22:59ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-08-0127e66100e6610010.2196/66100AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical RecommendationsBo Caohttp://orcid.org/0000-0001-9338-3271Russell Greinerhttp://orcid.org/0000-0001-8327-934XAndrew Greenshawhttp://orcid.org/0000-0002-9097-900XJie Suihttp://orcid.org/0000-0002-4031-4456 AbstractRecent 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.https://www.jmir.org/2025/1/e66100 |
| spellingShingle | Bo Cao Russell Greiner Andrew Greenshaw Jie Sui AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations Journal of Medical Internet Research |
| title | AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |
| title_full | AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |
| title_fullStr | AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |
| title_full_unstemmed | AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |
| title_short | AI and Machine Learning Terminology in Medicine, Psychology, and Social Sciences: Tutorial and Practical Recommendations |
| title_sort | ai and machine learning terminology in medicine psychology and social sciences tutorial and practical recommendations |
| url | https://www.jmir.org/2025/1/e66100 |
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