Physics-Guided Deep Learning for Interpretable Biomedical Image Reconstruction and Pattern Recognition in Diagnostic Frameworks

This study introduces a physics-guided deep learning architecture designed for the simulation, reconstruction, and pattern recognition of biomedical images. By explicitly integrating physical priors into the learning model, the framework addresses the black-box nature of traditional artificial intel...

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Detalhes bibliográficos

Principais autores:	Akeel Qadir, Saad Arif, Prajoona Valsalan, Osama Khan
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Bioengineering
Assuntos:	AI-assisted diagnostic workflows automated disease classification biomedical image reconstruction clinical decision support systems deep learning-based image segmentation explainable artificial intelligence
Acesso em linha:	https://www.mdpi.com/2306-5354/13/4/457
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