Dataset size and splitting.

<div><p>Traditional clinical assessments often lack individualization, relying on standardized procedures that may not accommodate the diverse needs of patients, especially in early stages where personalized diagnosis could offer significant benefits. We aim to provide a machine-learning...

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Bibliographic Details
Main Author:	Devin Setiawan (22155445) (author)
Other Authors:	Yumiko Wiranto (22311263) (author), Jeffrey M. Girard (5403536) (author), Amber Watts (2620564) (author), Arian Ashourvan (6685232) (author)
Published:	2025
Subjects:	Biotechnology Sociology Cancer Biological Sciences not elsewhere classified Information Systems not elsewhere classified tailor feature selection shapley additive explanations individual patient characteristics heart failure dataset heart disease dataset feature selection methods 6 &# 8211 best additional features enhances diagnostic accuracy enhance diagnostic accuracy early diabetes dataset icare shows improvements synthetic dataset 1 early diabetes initial features icare shows including early early stages world datasets value analysis standardized procedures significant advantage roc curve individualized approaches icare achieved global approaches global approach diverse needs clinical assessments
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Dataset size and splitting.

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