Deep learning for automatic ICD coding: Review, opportunities and challenges.

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Bibliographic Details
Title: Deep learning for automatic ICD coding: Review, opportunities and challenges.
Authors: Li X; School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, 116026, China., Zhang Y; School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, 116026, China. Electronic address: zhangyijia@dlmu.edu.cn., Hou X; School of Artificial Intelligence, Dalian Maritime University, Dalian, Liaoning, 116026, China., Wang S; School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, 116026, China., Lin H; School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116024, China.
Source: Artificial intelligence in medicine [Artif Intell Med] 2025 Oct; Vol. 168, pp. 103187. Date of Electronic Publication: 2025 Jul 10.
Publication Type: Journal Article; Systematic Review; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Science Publishing Country of Publication: Netherlands NLM ID: 8915031 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2860 (Electronic) Linking ISSN: 09333657 NLM ISO Abbreviation: Artif Intell Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1873-2860
DOI:10.1016/j.artmed.2025.103187