A Responsible Framework for Assessing, Selecting, and Explaining Machine Learning Models in Cardiovascular Disease Outcomes Among People With Type 2 Diabetes: Methodology and Validation Study
Abstract BackgroundBuilding machine learning models that are interpretable, explainable, and fair is critical for their trustworthiness in clinical practice. Interpretability, which refers to how easily a human can comprehend the mechanism by which a model makes predictions, i...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-06-01
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| Series: | JMIR Medical Informatics |
| Online Access: | https://medinform.jmir.org/2025/1/e66200 |
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