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HiMAL: Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting Alzheimer's disease progression.

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Title: HiMAL: Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting Alzheimer's disease progression.
Authors: Kumar S; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States., Yu SC; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States., Michelson A; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.; Division of Pulmonary and Critical Care, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States., Kannampallil T; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.; Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO 63110, United States., Payne PRO; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.
Source: JAMIA open [JAMIA Open] 2024 Sep 17; Vol. 7 (3), pp. ooae087. Date of Electronic Publication: 2024 Sep 17 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press on behalf of the American Medical Informatics Association Country of Publication: United States NLM ID: 101730643 Publication Model: eCollection Cited Medium: Internet ISSN: 2574-2531 (Electronic) Linking ISSN: 25742531 NLM ISO Abbreviation: JAMIA Open Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Kumar+S%22">Kumar S</searchLink>; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.<br /><searchLink fieldCode="AU" term="%22Yu+SC%22">Yu SC</searchLink>; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.<br /><searchLink fieldCode="AU" term="%22Michelson+A%22">Michelson A</searchLink>; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.; Division of Pulmonary and Critical Care, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States.<br /><searchLink fieldCode="AU" term="%22Kannampallil+T%22">Kannampallil T</searchLink>; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.; Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO 63110, United States.<br /><searchLink fieldCode="AU" term="%22Payne+PRO%22">Payne PRO</searchLink>; Department of Computer Science and Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States.; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, United States.
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