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https://hdl.handle.net/10356/180472| Title: | Ten quick tips for ensuring machine learning model validity | Authors: | Goh, Wilson Wen Bin Kabir, Mohammad Neamul Yoo, Sehwan Wong, Limsoon |
Keywords: | Medicine, Health and Life Sciences | Issue Date: | 2024 | Source: | 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 | Project: | IAF-PP RS08/21 |
Journal: | PLoS Computational Biology | Abstract: | 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. | URI: | https://hdl.handle.net/10356/180472 | ISSN: | 1553-734X | DOI: | 10.1371/journal.pcbi.1012402 | Schools: | Lee Kong Chian School of Medicine (LKCMedicine) School of Biological Sciences |
Research Centres: | Center for Biomedical Informatics Center of AI in Medicine |
Rights: | © 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. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
| Appears in Collections: | LKCMedicine Journal Articles |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| journal.pcbi.1012402.pdf | 1.97 MB | Adobe PDF |  View/Open |
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