AI-driven analysis by identifying risk factors of VL relapse in HIV co-infected patients

AI-driven analysis by identifying risk factors of VL relapse in HIV co-infected patients

Abstract Visceral Leishmaniasis (VL), also known as Kala-Azar, poses a significant global public health challenge and is a neglected disease, with relapses and treatment failures leading to increased morbidity and mortality. This study introduces an explainable machine learning approach to predict V...

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Bibliographic Details
Main Authors: Abhishek Kumar, Sanchita Mondal, Debnarayan Khatua, Debashree Guha, Budhaditya Mukherjee, Arista Lahiri, Dilip K. Prasad, Arif Ahmed Sekh
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
VL relapse
Relapse prediction
Risk factors for VL relapse
Cox regression
Explainable machine learning
Online Access:https://doi.org/10.1038/s41598-025-07406-7
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https://doi.org/10.1038/s41598-025-07406-7

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