Ten quick tips for ensuring machine learning model validity

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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Bibliographic Details
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
Description
Summary: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.

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