CLinNET: An Interpretable and Uncertainty-Aware Deep Learning Framework for Multi-Modal Clinical Genomics.
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| Title: | CLinNET: An Interpretable and Uncertainty-Aware Deep Learning Framework for Multi-Modal Clinical Genomics. |
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| Authors: | Bakhshayeshi I; UNSW BioMedical Machine Learning Lab (BML), School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia., Hosseini MM; Remote Internship in UNSW BioMedical Machine Learning Lab, School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia., Argha A; School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia.; Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW, 2052, Australia., Zahedi R; UNSW BioMedical Machine Learning Lab (BML), School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia., Lovell NH; School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia.; Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW, 2052, Australia., Alinejad-Rokny H; UNSW BioMedical Machine Learning Lab (BML), School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia. |
| Source: | Advanced science (Weinheim, Baden-Wurttemberg, Germany) [Adv Sci (Weinh)] 2026 Feb; Vol. 13 (12), pp. e12842. Date of Electronic Publication: 2026 Jan 28. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: WILEY-VCH Country of Publication: Germany NLM ID: 101664569 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2198-3844 (Electronic) Linking ISSN: 21983844 NLM ISO Abbreviation: Adv Sci (Weinh) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2198-3844 |
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| DOI: | 10.1002/advs.202512842 |
