https://doi.org/10.7490/f1000research.1119752.1
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Magdi Mekki Y and Sharma N. Development of an explainable machine learning model for predicting 10-year risk of death in NHANES I participants: A clinician engineer’s guide to synergizing clinical expertise, engineering innovation, and data science [version 1; not peer reviewed]. F1000Research 2024, 13:666 (poster) (https://doi.org/10.7490/f1000research.1119752.1)
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Development of an explainable machine learning model for predicting 10-year risk of death in NHANES I participants: A clinician engineer’s guide to synergizing clinical expertise, engineering innovation, and data science

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Published 21 Jun 2024

Development of an explainable machine learning model for predicting 10-year risk of death in NHANES I participants: A clinician engineer’s guide to synergizing clinical expertise, engineering innovation, and data science

[version 1; not peer reviewed]

Yosra Magdi Mekki1, Neel Sharma
Author Affiliations
1 College of Medicine, Qatar University, Doha, Doha, Qatar
Presented at
Artificial Intelligence and Medicine: Bringing Digital Breakthroughs to the Bedside, 2023
Competing Interests

No competing interests were disclosed

Keywords
machine learning, NHANES I, clinician engineering, explainable model
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