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DOI 10.1016/s2214-109x(25)00473-5

Медицинская библиотека · The Lancet. Global health · 2026

Research priorities for data science and artificial intelligence in global health: an international consensus exercise.

Song Peige, Jiang Denan, Zhou Jiali, Zhu Yajie, Manaf Rosliza Abdul, Bojude Danladi Adamu, Agbre-Yace Marie Laurette, Ali Sajjad, Allen Omolade, Anyasodor Anayochukwu Edward, Aranda Zeus, Bahattab Awsan, Bodomo Adams, Borrescio-Higa Florencia, Buchtova Marie, Buljan Nataša, Deshmukh Vaishali, Díaz-Castro Lina, Cheema Sohaila, Ekezie Winifred, Ganasegeran Kurubaran, Ganesan Balasankar, Glasnović Anton, Graham Christopher J, Htay Mila Nu Nu, Igwesi-Chidobe Chinonso, Iversen Per Ole, Islam Mohammad Mainul, Karim Abdulkarim Jafar, Kalpič Brane, Kanma-Okafor Oluchi, Lanza Giuseppe, Luz Saturnino, Mahikul Wiriya, Mladenić Dunja, Manyara Anthony Muchai, Munipalli Bala, Myburgh Nellie, Ng Zhi Xiang, Nikolopoulos Georgios, Park Chulwoo, Park Jay J, Peprah Prince, Rudan Klara, Shah Syed Ahmar, Shi Ting, Tiglic Gregor Š, Sutan Rosnah, Tsanas Athanasios, Tibble Holly, Khpalwak Abdul Tawab, Tomlinson Mark, Vento Sandro, Glasnović Josipa Vlasac, Wang Liang, Xu Jingyi, Zhang Jianrong, Zhang Yanfeng, Sheikh Eamon, Ozoh Obianuju B, Tsiachristas Apostolos, Adeloye Davies, Kerr Steven, Sanwalka Mili, Orešković Stjepan, Sheikh Aziz, Rudan Igor

Consensus StatementСтатьяОбзорПеревод в очереди

Аннотация

Applications of data science and artificial intelligence (AI) in global health are expanding, yet research remains fragmented and often misaligned with the needs of low-income and middle-income countries (LMICs). To address this misalignment, we conducted a global research priority-setting exercise using the Child Health and Nutrition Research Initiative (CHNRI) method. 155 research ideas were scored by 51 experts based on feasibility, potential impact on disease burden, paradigm shift potential, implementation potential, and equity. Top-ranked priorities focused on epidemic preparedness, including AI-based outbreak prediction, improved diagnostics for infectious diseases, and early-warning systems. Other highly ranked topics included AI-assisted resource allocation, telemedicine, culturally adapted mobile health services, and chronic disease management tools. Experts from LMICs prioritised infectious disease control and diagnostic equity, whereas experts from high-income countries emphasised infrastructure and climate-related analytics. The resulting agenda provides a roadmap for aligning AI and data science research with global health priorities, particularly in LMICs.

Для цитирования: Song Peige, Jiang Denan, Zhou Jiali, Zhu Yajie, Manaf Rosliza Abdul, Bojude Danladi Adamu, Agbre-Yace Marie Laurette, Ali Sajjad, Allen Omolade, Anyasodor Anayochukwu Edward, Aranda Zeus, Bahattab Awsan, Bodomo Adams, Borrescio-Higa Florencia, Buchtova Marie, Buljan Nataša, Deshmukh Vaishali, Díaz-Castro Lina, Cheema Sohaila, Ekezie Winifred, Ganasegeran Kurubaran, Ganesan Balasankar, Glasnović Anton, Graham Christopher J, Htay Mila Nu Nu, Igwesi-Chidobe Chinonso, Iversen Per Ole, Islam Mohammad Mainul, Karim Abdulkarim Jafar, Kalpič Brane, Kanma-Okafor Oluchi, Lanza Giuseppe, Luz Saturnino, Mahikul Wiriya, Mladenić Dunja, Manyara Anthony Muchai, Munipalli Bala, Myburgh Nellie, Ng Zhi Xiang, Nikolopoulos Georgios, Park Chulwoo, Park Jay J, Peprah Prince, Rudan Klara, Shah Syed Ahmar, Shi Ting, Tiglic Gregor Š, Sutan Rosnah, Tsanas Athanasios, Tibble Holly, Khpalwak Abdul Tawab, Tomlinson Mark, Vento Sandro, Glasnović Josipa Vlasac, Wang Liang, Xu Jingyi, Zhang Jianrong, Zhang Yanfeng, Sheikh Eamon, Ozoh Obianuju B, Tsiachristas Apostolos, Adeloye Davies, Kerr Steven, Sanwalka Mili, Orešković Stjepan, Sheikh Aziz, Rudan Igor. Research priorities for data science and artificial intelligence in global health: an international consensus exercise.. The Lancet. Global health. 2026. DOI: 10.1016/s2214-109x(25)00473-5.

Предметные рубрики MeSH

HumansArtificial IntelligenceData ScienceDeveloping CountriesGlobal HealthResearch
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