Adaptive geometric-attention network for two-stage lung nodule segmentation and malignancy classification in federated healthcare IoT edge environments.
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| Title: | Adaptive geometric-attention network for two-stage lung nodule segmentation and malignancy classification in federated healthcare IoT edge environments. |
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| Authors: | Sufyan M; College of Computer Science, Beijing University of Technology, Beijing, China., Qian J; College of Computer Science, Beijing University of Technology, Beijing, China., Li J; College of Computer Science, Beijing University of Technology, Beijing, China., Imran A; College of Computer Science, Beijing University of Technology, Beijing, China., Sabah F; College of Computer Science, Beijing University of Technology, Beijing, China., Sarwar R; OTEHM, Manchester Metropolitan University, Manchester, United Kingdom. |
| Source: | PloS one [PLoS One] 2026 Jul 10; Vol. 21 (7), pp. e0341096. Date of Electronic Publication: 2026 Jul 10 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0341096 |
