Applying Machine Learning to Predict Loss to Follow-Up Among People Living With HIV in Haiti Using a National Electronic Medical Record Cohort.
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| Title: | Applying Machine Learning to Predict Loss to Follow-Up Among People Living With HIV in Haiti Using a National Electronic Medical Record Cohort. |
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| Authors: | Wu J; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Washington, DC, United States., Shaw B; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Washington, DC, United States., Oni B; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Washington, DC, United States., Jean-Charles K; Solutions S.A., Port-au-Prince, Haiti., Dorestan D; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti., Bien-Aime M; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti., Compere-Louis D; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Washington, DC, United States., Dorce V; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti., Jean-Pierre V; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti., Joseph ME; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti., Labbe NR; Center for Global Health Practice and Impact (CGHPI), Georgetown University Medical Center, Port-au-Prince, Haiti. |
| Source: | International journal of public health [Int J Public Health] 2026 Apr 28; Vol. 71, pp. 1609496. Date of Electronic Publication: 2026 Apr 28 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101304551 Publication Model: eCollection Cited Medium: Internet ISSN: 1661-8564 (Electronic) Linking ISSN: 16618556 NLM ISO Abbreviation: Int J Public Health Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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