{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T06:04:34Z","timestamp":1780639474989,"version":"3.54.1"},"reference-count":16,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T00:00:00Z","timestamp":1780617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Late presentation and delayed antiretroviral therapy (ART) initiation among people living with HIV (PLWH) are associated with increased morbidity, mortality, and transmission risk. Identifying individuals at high risk of delayed care or severe immunosuppression (CD4\u202f&amp;lt;\u202f200 cells\/\u03bcL) could enable targeted interventions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and validate an artificial intelligence (AI)-based risk stratification tool using routinely collected data to identify PLWH at high risk of delayed ART initiation or advanced immunosuppression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study using de-identified data from HIV-positive individuals (2016 onward). A composite high-risk outcome was defined as delayed ART initiation or baseline CD4\u202f&amp;lt;\u202f200 cells\/\u03bcL. Multiple classifiers\u2014including logistic regression, XGBoost, LightGBM, CatBoost, multilayer perceptron, and HistGradientBoosting\u2014were trained with five-fold stratified cross-validation. A stacking ensemble incorporating six base models and a LightGBM meta-learner was evaluated. Discrimination (AUC-ROC, AUC-PR), calibration, and clinical utility (decision curve analysis) were assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 5,436 eligible participants, 61.2% were high-risk. The stacking ensemble achieved an AUC-ROC of 0.915, AUC-PR of 0.950, accuracy of 0.815, and F1 score of 0.858. At \u226590% sensitivity, precision was 0.810. Calibration was good across deciles; decision curve analysis showed net benefit superior to treat-all or treat-none strategies. Baseline CD4 count, age, and transmission route were the strongest predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>An AI-based risk stratification tool using routinely collected data can identify PLWH at high risk of delayed ART or advanced immunosuppression with strong performance and clinical utility. Prospective validation and equity assessment are needed before implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1835733","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:38:37Z","timestamp":1780637917000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"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"],"prefix":"10.3389","volume":"14","author":[{"given":"Jinling","family":"Yin","sequence":"first","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"Drug Clinical Trial Institution Office, Xi\u2019an Chest Hospital","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanhuan","family":"Ba","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Information Management Office, Northwestern Polytechnical University","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangxiao","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e207","DOI":"10.1016\/s2352-3018(25)00265-6","article-title":"Reducing HIV incidence and mortality: two sides of the same coin in the approach to ending AIDS","volume":"13","author":"Jarvis","year":"2025","journal-title":"Lancet HIV"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"100175","DOI":"10.1016\/j.lana.2021.100175","article-title":"Clinical effects of durability of immunosuppression in virologically suppressed ART-initiating persons with HIV in Latin America. A retrospective cohort study","volume":"8","author":"Caro-Vega","year":"2022","journal-title":"Lancet Regional Health Americas"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"e269","DOI":"10.1016\/S2352-3018(22)00003-0","article-title":"Delayed presentation of HIV among older individuals: a growing problem","volume":"9","author":"Justice","year":"2022","journal-title":"Lancet HIV"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"e0000720","DOI":"10.1371\/journal.pgph.0000720","article-title":"Machine learning with routine electronic medical record data to identify people at high risk of disengagement from HIV care in Tanzania","volume":"2","author":"Fahey","year":"2022","journal-title":"PLOS Global Public Health"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1007\/s11904-019-00454-5","article-title":"A review of differentiated service delivery for HIV treatment: effectiveness, mechanisms, targeting, and scale","volume":"16","author":"Roy","year":"2019","journal-title":"Curr HIV AIDS Rep"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1186\/s13643-019-1210-6","article-title":"Differentiated models of service delivery for antiretroviral treatment of HIV in sub-Saharan Africa: a rapid review protocol","volume":"8","author":"Long","year":"2019","journal-title":"Syst Rev"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s10461-021-03399-2","article-title":"Modeling the impact of social determinants of health on HIV","volume":"25","author":"Hogan","year":"2021","journal-title":"AIDS Behav"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"e70045","DOI":"10.1002\/jia2.70045","article-title":"Artificial intelligence for HIV care: a global systematic review of current studies and emerging trends","volume":"28","author":"Ngcobo","year":"2025","journal-title":"J Int AIDS Soc"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s44263-025-00184-4","article-title":"Evaluating predictive performance, validity, and applicability of machine learning models for predicting HIV treatment interruption: a systematic review","volume":"3","author":"Kwarah","year":"2025","journal-title":"BMC Glob Public Health"},{"key":"ref10","first-page":"18","author":"Caruana","year":"2004"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/s0893-6080(05)80023-1","article-title":"Stacked generalization","volume":"5","author":"Wolpert","year":"1992","journal-title":"Neural Netw"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1016\/j.compbiomed.2017.11.001","article-title":"A survey of machine learning applications in HIV clinical research and care","volume":"91","author":"Bisaso","year":"2017","journal-title":"Comput Biol Med"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s11904-020-00490-6","article-title":"Artificial intelligence and machine learning for HIV prevention: emerging approaches to ending the epidemic","volume":"17","author":"Marcus","year":"2020","journal-title":"Curr HIV\/AIDS Rep"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1186\/s12916-019-1466-7","article-title":"Calibration: the Achilles heel of predictive analytics","volume":"17","author":"Van Calster","year":"2019","journal-title":"BMC Med"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1177\/0272989X06295361","article-title":"Decision curve analysis: a novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med Decis Mak"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1186\/s13643-025-03062-0","article-title":"Clients' satisfaction with HIV differentiated service delivery models and associated factors in sub-Saharan Africa: a protocol for a systematic review and meta-analysis","volume":"15","author":"Kaonga","year":"2026","journal-title":"Syst Rev"}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1835733\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:38:38Z","timestamp":1780637918000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1835733\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,5]]},"references-count":16,"alternative-id":["10.3389\/fpubh.2026.1835733"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2026.1835733","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,5]]},"article-number":"1835733"}}