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In this paper, we present nine concise and actionable tips to help researchers build ML systems that are technically sound but ethically responsible, and contextually appropriate for biomedical applications. These tips address the multifaceted nature of trustworthiness, emphasizing the importance of considering all potential consequences, recognizing the limitations of current methods, taking into account the needs of all involved stakeholders, and following open science practices. We discuss technical, ethical, and domain-specific challenges, offering guidance on how to define trustworthiness and how to mitigate sources of untrustworthiness. By embedding trustworthiness into every stage of the ML pipeline \u2013 from research design to deployment \u2013 these recommendations aim to support both novice and experienced practitioners in creating ML systems that can be relied upon in biomedical science.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013624","type":"journal-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:30:29Z","timestamp":1761845429000},"page":"e1013624","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Nine quick tips for trustworthy machine learning in the biomedical sciences"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8445-395X","authenticated-orcid":true,"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":[[2025,10,30]]},"reference":[{"key":"pcbi.1013624.ref001","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9781107298019","volume-title":"Understanding machine learning: from theory to algorithms","author":"S Shalev-Shwartz","year":"2014"},{"issue":"9","key":"pcbi.1013624.ref002","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1038\/s41591-022-01981-2","article-title":"Multimodal biomedical AI","volume":"28","author":"JN Acosta","year":"2022","journal-title":"Nat Med"},{"issue":"10","key":"pcbi.1013624.ref003","article-title":"Large language model influence on diagnostic reasoning: a randomized clinical trial","volume":"7","author":"E Goh","year":"2024","journal-title":"JAMA Netw Open"},{"key":"pcbi.1013624.ref004","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkad1011","article-title":"AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences","volume":"52","author":"M Varadi","year":"2024","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1013624.ref005","volume-title":"Artificial intelligence: a modern approach","author":"P Norvig","year":"2020","edition":"4"},{"issue":"2","key":"pcbi.1013624.ref006","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/S0933-3657(00)00059-2","article-title":"AI planning and scheduling in the medical hospital environment","volume":"20","author":"CD Spyropoulos","year":"2000","journal-title":"Artif Intell Med"},{"key":"pcbi.1013624.ref007","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.jbi.2014.07.017","article-title":"Creating hospital-specific customized clinical pathways by applying semantic reasoning to clinical data","volume":"52","author":"H Wang","year":"2014","journal-title":"J Biomed Inform"},{"key":"pcbi.1013624.ref008","doi-asserted-by":"crossref","DOI":"10.1142\/9356","volume-title":"Causality, correlation and artificial intelligence for rational decision making","author":"T Marwala","year":"2015"},{"issue":"6556","key":"pcbi.1013624.ref009","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1126\/science.abi5052","article-title":"Making machine learning trustworthy","volume":"373","author":"B Eshete","year":"2021","journal-title":"Science"},{"issue":"2","key":"pcbi.1013624.ref010","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MIS.2009.36","article-title":"The unreasonable effectiveness of data","volume":"24","author":"A Halevy","year":"2009","journal-title":"IEEE Intell Syst"},{"key":"pcbi.1013624.ref011","unstructured":"European Commission. 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