Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images

Abstract Birth complications, particularly jaundice, are one of the leading causes of adolescent death and disease all over the globe. The main severity of these illnesses may diminish if scholars study more about their sources and progress toward effective treatment. Assured developments were prepa...

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Bibliographic Details
Main Authors: M. Eliazer, Sibi Amaran, K. Sreekumar, A. Vikram, Gyanendra Prasad Joshi, Woong Cho
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Vision transformer
Jaundice image classification
Neonatal
Kernel extreme learning machine
Healthcare
Enhanced coati optimisation algorithm
Online Access:https://doi.org/10.1038/s41598-025-08342-2
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https://doi.org/10.1038/s41598-025-08342-2

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