{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T13:39:41Z","timestamp":1791725981947,"version":"4.3.4"},"reference-count":107,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T00:00:00Z","timestamp":1767744000000},"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. Med."],"abstract":"<jats:p>\n                    Tuberculosis, an infectious disease caused by\n                    <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                    , poses a major global health challenge. Despite being largely controlled for several decades, tuberculosis has experienced a resurgence in recent years. China has the second highest incidence of tuberculosis globally, with a prevalence of 459 cases per 100,000 individuals aged 15 years old. Chest radiography and pathology are essential tools for its detection and diagnosis. However, the small size and low number of tubercle bacilli make detection and identification under a microscope challenging, often resulting in low detection rates and false diagnoses. Artificial intelligence (AI) has emerged as a promising tool to improve the accuracy and sensitivity of tuberculosis detection. This review provides a comprehensive overview of the literature on the use of machine learning-based models for the automatic detection of tuberculosis bacilli, emphasizing the advantages of integrating in tuberculosis diagnosis. Understanding the onset and progression of tuberculosis is crucial to developing effective strategies for its diagnosis, treatment, and prevention.\n                  <\/jats:p>","DOI":"10.3389\/fmed.2025.1569615","type":"journal-article","created":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T06:51:43Z","timestamp":1767768703000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Tuberculosis diagnosis using artificial intelligence: current trends and future prospects"],"prefix":"10.3389","volume":"12","author":[{"given":"Onesime","family":"Mbulayi","sequence":"first","affiliation":[{"name":"Department of Mathematics, Statistics and Informatics, University of Kinshasa","place":["Kinshasa, Democratic Republic of Congo"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saint-Jean","family":"Djungu","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Statistics and Informatics, University of Kinshasa","place":["Kinshasa, Democratic Republic of Congo"]},{"name":"Applied Informatics Research Center (CRIA), University of Kinshasa","place":["Kinshasa, Democratic Republic of Congo"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Loukia","family":"Aketi","sequence":"additional","affiliation":[{"name":"Cardio-pulmonary and Infectious Diseases Unit, Department of Pediatrics, University of Kinshasa","place":["Kinshasa, Democratic Republic of Congo"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed Amine","family":"Koulali","sequence":"additional","affiliation":[{"name":"Laboratoire de Modelisation et Calcul Scientifique (LMCS), ENSAO, Mohammed First University","place":["Rabat, Morocco"]},{"name":"College of Computing, Mohammed VI Polytechnic University","place":["Ben Guerir, Morocco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanae","family":"Azzaoui","sequence":"additional","affiliation":[{"name":"Laboratoire Genie Electrique et Maintenance (LGEM), ESEF, Mohammed First University","place":["Oujda, Morocco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rim","family":"Koulali","sequence":"additional","affiliation":[{"name":"LIS Laboratory, Faculty of Sciences Ain Chock (FSAC), Hassan II University of Casablanca","place":["Casablanca, Morocco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"El Mzibri","sequence":"additional","affiliation":[{"name":"Centre Nationale de l\u2019Energie, des Sciences et des Technologies Nucleaires (CNESTEN)","place":["Rabat, Morocco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imane","family":"Chaoui","sequence":"additional","affiliation":[{"name":"Centre Nationale de l\u2019Energie, des Sciences et des Technologies Nucleaires (CNESTEN)","place":["Rabat, Morocco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yahya","family":"Tayalati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,1,7]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.1136\/bjsports-2020-102955","article-title":"World Health Organization 2020 guidelines on physical activity and sedentary behaviour.","volume":"54","author":"Bull","year":"2020","journal-title":"Br J Sports Med."},{"key":"B2","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1111\/bjd.15510","article-title":"The global burden of tuberculosis: Results from the Global Burden of Disease Study 2015.","volume":"18","author":"Kyu","year":"2018","journal-title":"Lancet Infect Dis."},{"key":"B3","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/s41479-024-00133-z","article-title":"Early detection of tuberculosis: A systematic review.","volume":"16","author":"Yayan","year":"2024","journal-title":"Pneumonia."},{"key":"B4","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1164\/rccm.202006-2394PP","article-title":"The epidemiological importance of subclinical tuberculosis. 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