Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
Year: 2016
Type: article
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funders: National Science Foundation, Patient-Centered Outcomes Research Institute, National Institutes of Health, U.S. Food and Drug Administration, Agency for Healthcare Research and Quality, National Institute of Mental Health, National Human Genome Research Institute, National Institute of General Medical Sciences, U.S. National Library of Medicine, National Center for Complementary and Integrative Health
Awards: G1023556497, G183956947, G1875582626, SCH: INT: Collaborative Research: High-throughput Phenotyping on Electronic Health Records using Multi-Tensor Factorization, G2310098089, G2424387874, National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms, G2956969645, G2998518889, G4350769723, G5054551166, G5182012706, G55335095, Beyond PheWAS: Recognition of Phenotype Patterns for Discovery and Translation, G6887866007, UNDERSTANDING THE BIDIRECTIONAL RELATIONSHIP BETWEEN DEPRESSION AND HEART FAILURE, G851032352, XPS: FULL: DSD: A Parallel Tensor Infrastructure (ParTI!) for Data Analysis, G9000000364, G9000008291, G9000050286, G9000117499, G9000167145, G9000215899, G9000284903
OpenAlex ID: W2467651252