Machine learning risk stratification to identify people living with HIV at high risk of delayed ART and advanced immunosuppression: a precision public health approach.

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Bibliographic Details
Title: Machine learning risk stratification to identify people living with HIV at high risk of delayed ART and advanced immunosuppression: a precision public health approach.
Authors: Yin J; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Li T; Drug Clinical Trial Institution Office, Xi'an Chest Hospital, Xi'an, Shaanxi, China., Jin J; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Chen J; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Ba H; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Zhang Y; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Li J; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China., Liu H; Information Management Office, Northwestern Polytechnical University, Xi'an, Shaanxi, China., Ma K; Department of Infectious Diseases, The Eighth's Hospital of Xi'an, Xi'an, Shaanxi, China.
Source: Frontiers in public health [Front Public Health] 2026 Jun 05; Vol. 14, pp. 1835733. Date of Electronic Publication: 2026 Jun 05 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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