View in EDS

KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.

Saved in:
Bibliographic Details
Title: KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.
Authors: Li J; The Department of Radiology, Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Xueyuan West Road, Wenzhou, 325027, China.; The Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China., Pan R; Hangzhou Normal University, Hangzhou, China., Tian F; Sichuan Agricultural University, Yucheng, China., Pan P; The Department of Radiology, Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Xueyuan West Road, Wenzhou, 325027, China.; Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, China., Yan Z; The Department of Radiology, Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Xueyuan West Road, Wenzhou, 325027, China. yanzhihanwz@163.com.; Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, China. yanzhihanwz@163.com.
Source: Pediatric radiology [Pediatr Radiol] 2026 Feb 20. Date of Electronic Publication: 2026 Feb 20.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 0365332 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1998 (Electronic) Linking ISSN: 03010449 NLM ISO Abbreviation: Pediatr Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1432-1998
DOI:10.1007/s00247-026-06534-0