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Development of a Machine Learning Modeling Tool for Predicting HIV Incidence Using Public Health Data From a County in the Southern United States.

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Title: Development of a Machine Learning Modeling Tool for Predicting HIV Incidence Using Public Health Data From a County in the Southern United States.
Authors: Saldana CS; Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA., Burkhardt E; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Pennisi A; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Oliver K; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Olmstead J; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Holland DP; Division of Primary Care, Mercy Care Health Systems, Atlanta, Georgia, USA.; Fulton County Board of Health, Communicable Disease Prevention Branch, Atlanta, Georgia, USA., Gettings J; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Mauck D; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Austin D; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Wortley P; Epidemiology Division, Georgia Department of Public Health, Atlanta, Georgia, USA., Ochoa KVS; School of Architecture, College of Design, Construction, and Planning, University of Florida, Gainesville, Florida, USA.
Source: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America [Clin Infect Dis] 2024 Sep 26; Vol. 79 (3), pp. 717-726.
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 9203213 Publication Model: Print Cited Medium: Internet ISSN: 1537-6591 (Electronic) Linking ISSN: 10584838 NLM ISO Abbreviation: Clin Infect Dis Subsets: MEDLINE
Database: MEDLINE Ultimate
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