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...

Fuld beskrivelse

Bibliografiske detaljer

Principais autores:	Pallavi Patil, S. Supreeth, Kirankumari Patil
Format:	Artigo
Sprog:	Inglês
Udgivet:	Springer 2026-01-01
Serier:	Discover Artificial Intelligence
Fag:	Deep learning Pulmonary nodule segmentation Tornado optimizer with coriolis force Severity assessment SHapley Additive exPlanations
Online adgang:	https://doi.org/10.1007/s44163-025-00749-0
Tags:	Tilføj Tag Ingen Tags, Vær først til at tagge denne postø!