An optimized hybrid deep learning model with SHapley Additive exPlanations for pulmonary fibrosis nodule segmentation and severity assessment

Abstract Pulmonary nodule segmentation and severity assessment are crucial for the diagnosis and monitoring of pulmonary fibrosis, enabling accurate identification of fibrotic changes and evaluation of disease progression. Current architectures frequently face substantial computational demands, limi...

Descrizione completa

Dettagli Bibliografici

Autori principali:	Pallavi Patil, S. Supreeth, Kirankumari Patil
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2026-01-01
Serie:	Discover Artificial Intelligence
Soggetti:	Deep learning Pulmonary nodule segmentation Tornado optimizer with coriolis force Severity assessment SHapley Additive exPlanations
Accesso online:	https://doi.org/10.1007/s44163-025-00749-0
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!