An interpretable predictive deep learning platform for pediatric metabolic diseases.

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Bibliographic Details
Title: An interpretable predictive deep learning platform for pediatric metabolic diseases.
Authors: Javidi H; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, United States.; Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH 44115, United States.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44195, United States., Mariam A; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, United States.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44195, United States., Alkhaled L; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44195, United States.; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH 44195, United States., Pantalone KM; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44195, United States.; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH 44195, United States., Rotroff DM; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, United States.; Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH 44115, United States.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44195, United States.; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH 44195, United States.
Source: Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2024 May 20; Vol. 31 (6), pp. 1227-1238.
Publication Type: Journal Article; Research Support, N.I.H., Extramural
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE
Database: MEDLINE Ultimate
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Description
ISSN:1527-974X
DOI:10.1093/jamia/ocae049