Ten quick tips for ensuring machine learning model validity

Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips descri...

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Main Authors:	Goh, Wilson Wen Bin, Kabir, Mohammad Neamul, Yoo, Sehwan, Wong, Limsoon
Other Authors:	Lee Kong Chian School of Medicine (LKCMedicine)
Format:	Article
Language:	English
Published:	2024
Subjects:	Medicine, Health and Life Sciences Artificial Intelligence Computational Biology
Online Access:	https://hdl.handle.net/10356/180472
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1804722024-10-13T15:37:40Z Ten quick tips for ensuring machine learning model validity Goh, Wilson Wen Bin Kabir, Mohammad Neamul Yoo, Sehwan Wong, Limsoon Lee Kong Chian School of Medicine (LKCMedicine) School of Biological Sciences Center for Biomedical Informatics Center of AI in Medicine Medicine, Health and Life Sciences Artificial Intelligence Computational Biology Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips described here discuss useful practices on how to check AI/ ML models from 2 perspectives—the user and the developer. Ministry of Education (MOE) National Research Foundation (NRF) Published version This research/project is supported by the National Research Foundation, Singapore under its Industry Alignment Fund - Pre-positioning (IAF-PP) Funding Initiative. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of National Research Foundation Singapore. WWBG acknowledges support from a Ministry of Education (MOE), Singapore Tier 1 grant (Grant No. RS08/21). LW acknowledges support from a Kwan Im Thong Hood Cho Temple Professorship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 2024-10-08T07:07:58Z 2024-10-08T07:07:58Z 2024 Journal Article Goh, W. W. B., Kabir, M. N., Yoo, S. & Wong, L. (2024). Ten quick tips for ensuring machine learning model validity. PLoS Computational Biology, 20, e1012402-. https://dx.doi.org/10.1371/journal.pcbi.1012402 1553-734X https://hdl.handle.net/10356/180472 10.1371/journal.pcbi.1012402 20 2-s2.0-85204347081 20 e1012402 en IAF-PP RS08/21 PLoS Computational Biology © 2024 Goh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Medicine, Health and Life Sciences Artificial Intelligence Computational Biology
spellingShingle	Medicine, Health and Life Sciences Artificial Intelligence Computational Biology Goh, Wilson Wen Bin Kabir, Mohammad Neamul Yoo, Sehwan Wong, Limsoon Ten quick tips for ensuring machine learning model validity
description	Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips described here discuss useful practices on how to check AI/ ML models from 2 perspectives—the user and the developer.
author2	Lee Kong Chian School of Medicine (LKCMedicine)
author_facet	Lee Kong Chian School of Medicine (LKCMedicine) Goh, Wilson Wen Bin Kabir, Mohammad Neamul Yoo, Sehwan Wong, Limsoon
format	Article
author	Goh, Wilson Wen Bin Kabir, Mohammad Neamul Yoo, Sehwan Wong, Limsoon
author_sort	Goh, Wilson Wen Bin
title	Ten quick tips for ensuring machine learning model validity
title_short	Ten quick tips for ensuring machine learning model validity
title_full	Ten quick tips for ensuring machine learning model validity
title_fullStr	Ten quick tips for ensuring machine learning model validity
title_full_unstemmed	Ten quick tips for ensuring machine learning model validity
title_sort	ten quick tips for ensuring machine learning model validity
publishDate	2024
url	https://hdl.handle.net/10356/180472
_version_	1814047451434188800

Ten quick tips for ensuring machine learning model validity

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