A compact and interpretable multi-source framework for heterogeneous medical image classification.

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Bibliographic Details
Title: A compact and interpretable multi-source framework for heterogeneous medical image classification.
Authors: Ayivi W; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China. w.ayivi@std.uestc.edu.cn.; Department of Information Systems and Operations Management, Vienna University of Economics and Business, 1020, Vienna, Austria. w.ayivi@std.uestc.edu.cn., Zhang X; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China. xlzhang@uestc.edu.cn., Ativi WX; School of Computer Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China., Sam F; School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China., Aligayev A; NOMATEN CoE, National Centre for Nuclear Research, 05-400, Otwock, Poland.; Scientific Research Center, Baku Engineering University, AZ0101, Baku, Azerbaijan.
Source: Scientific reports [Sci Rep] 2026 May 02; Vol. 16 (1). Date of Electronic Publication: 2026 May 02.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-51120-x