{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T18:55:10Z","timestamp":1776192910048,"version":"3.50.1"},"reference-count":93,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministero dell'Universit\u00e0 e della Ricerca of Italy","award":["FAIR (PE00000013) project"],"award-info":[{"award-number":["FAIR (PE00000013) project"]}]},{"name":"Ministero dell'Universit\u00e0 e della Ricerca of Italy","award":["Project Age-It (Ageing Well in an Ageing Society)"],"award-info":[{"award-number":["Project Age-It (Ageing Well in an Ageing Society)"]}]},{"name":"Ministero dell'Universit\u00e0 e della Ricerca of Italy","award":["ReGAInS grant"],"award-info":[{"award-number":["ReGAInS grant"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Machine learning has become a powerful tool for computational analysis in the biomedical sciences, with its effectiveness significantly enhanced by integrating domain-specific knowledge. This integration has give rise to informed machine learning, in contrast to studies that lack domain knowledge and treat all variables equally (uninformed machine learning). While the application of informed machine learning to bioinformatics and health informatics datasets has become more seamless, the likelihood of errors has also increased. To address this drawback, we present eight guidelines outlining best practices for employing informed machine learning methods in biomedical sciences. These quick tips offer recommendations on various aspects of informed machine learning analysis, aiming to assist researchers in generating more robust, explainable, and dependable results. Even if we originally crafted these eight simple suggestions for novices, we believe they are deemed relevant for expert computational researchers as well.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012711","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T18:23:43Z","timestamp":1736447023000},"page":"e1012711","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":8,"title":["Eight quick tips for biologically and medically informed machine learning"],"prefix":"10.1371","volume":"21","author":[{"given":"Luca","family":"Oneto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9655-7142","authenticated-orcid":true,"given":"Davide","family":"Chicco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,1,9]]},"reference":[{"issue":"158","key":"pcbi.1012711.ref001","doi-asserted-by":"crossref","first-page":"158rv11","DOI":"10.1126\/scitranslmed.3003528","article-title":"Computational medicine: translating models to clinical care.","volume":"4","author":"RL Winslow","year":"2012","journal-title":"Sci Transl Med"},{"issue":"6 Supplement","key":"pcbi.1012711.ref002","doi-asserted-by":"crossref","first-page":"3678","DOI":"10.1158\/1538-7445.AM2024-3678","article-title":"Beyond detection: AI-based classification of breast cancer invasiveness using cell-free orphan non-coding RNAs","volume":"84","author":"M Karimzadeh","year":"2024","journal-title":"Cancer Res"},{"issue":"6","key":"pcbi.1012711.ref003","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.cmrp.2019.11.005","article-title":"Current status and applications of artificial intelligence (AI) in medical field: an overview.","volume":"9","author":"A Haleem","year":"2019","journal-title":"Curr Med Res Pract."},{"issue":"11","key":"pcbi.1012711.ref004","doi-asserted-by":"crossref","first-page":"3271","DOI":"10.1177\/0962280217696115","article-title":"Leveraging electronic health records for predictive modeling of post-surgical complications.","volume":"27","author":"GB Weller","year":"2018","journal-title":"Stat Methods Med Res"},{"issue":"11","key":"pcbi.1012711.ref005","doi-asserted-by":"crossref","first-page":"3162","DOI":"10.1109\/JBHI.2020.2991763","article-title":"Matrix factorization-based technique for drug repurposing predictions","volume":"24","author":"G Ceddia","year":"2020","journal-title":"IEEE J Biomed Health Inform"},{"key":"pcbi.1012711.ref006","doi-asserted-by":"crossref","first-page":"104510","DOI":"10.1016\/j.ijmedinf.2021.104510","article-title":"The need to separate the wheat from the chaff in medical informatics: introducing a comprehensive checklist for the (self)-assessment of medical AI studies.","volume":"153","author":"F Cabitza","year":"2021","journal-title":"Int J Med Inform"},{"key":"pcbi.1012711.ref007","doi-asserted-by":"crossref","first-page":"e48175","DOI":"10.7554\/eLife.48175","article-title":"Ten common statistical mistakes to watch out for when writing or reviewing a manuscript.","volume":"8","author":"TR Makin","year":"2019","journal-title":"Elife."},{"issue":"10","key":"pcbi.1012711.ref008","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1145\/2347736.2347755","article-title":"A few useful things to know about machine learning.","volume":"55","author":"P. 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