Architecture of the iCARE framework.

Data were obtained from an incoming patient (I), and weights were generated for the pool of known cases in the Similarity Calculation Module (II). Using these sample weights, we generate a weighted logistic regression model for an inc...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Devin Setiawan (22155445) (author)
مؤلفون آخرون:	Yumiko Wiranto (22311263) (author), Jeffrey M. Girard (5403536) (author), Amber Watts (2620564) (author), Arian Ashourvan (6685232) (author)
منشور في:	2025
الموضوعات:	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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Architecture of the iCARE framework.

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