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Sökning: onr:"swepub:oai:DiVA.org:mdh-62030" > The use of artifici...

The use of artificial intelligence-based innovations in the health sector in Tanzania : A scoping review

Sukums, Felix (författare)
Muhimbili Univ Hlth & Allied Sci, Directorate Informat & Commun Technol, Box 65001, Dar Es Salaam, Tanzania.
Mzurikwao, Deogratias (författare)
Muhimbili Univ Hlth & Allied Sci, Biomed Engn Unit, Dar Es Salaam, Tanzania.
Sabas, Deodatus (författare)
Muhimbili Univ Hlth & Allied Sci, Directorate Lib Serv, Dar Es Salaam, Tanzania.
visa fler...
Chaula, Rebecca (författare)
Muhimbili Univ Hlth & Allied Sci, Directorate Informat & Commun Technol, Box 65001, Dar Es Salaam, Tanzania.
Mbuke, Juliana (författare)
Muhimbili Univ Hlth & Allied Sci, Directorate Informat & Commun Technol, Box 65001, Dar Es Salaam, Tanzania.
Kabika, Twaha (författare)
Muhimbili Univ Hlth & Allied Sci, Biomed Engn Unit, Dar Es Salaam, Tanzania.
Kaswija, John (författare)
Mwanza Coll Hlth & Allied Sci, Mwanza, Tanzania.
Ngowi, Bernard (författare)
Natl Inst Med Res, Muhimbili Med Res Ctr, Dar Es Salaam, Tanzania.
Noll, Josef (författare)
Univ Oslo, Dept Technol Syst, N-0318 Oslo, Norway.
Winkler, Andrea S. (författare)
Tech Univ Munich, Ctr Global Hlth, Dept Neurol, Munich, Germany.
Wamala, Sarah (författare)
Mälardalens universitet,Hälsa och välfärd
visa färre...
Muhimbili Univ Hlth & Allied Sci, Directorate Informat & Commun Technol, Box 65001, Dar Es Salaam, Tanzania Muhimbili Univ Hlth & Allied Sci, Biomed Engn Unit, Dar Es Salaam, Tanzania. (creator_code:org_t)
ELSEVIER SCI LTD, 2023
2023
Engelska.
Ingår i: Health Policy and Technology. - : ELSEVIER SCI LTD. - 2211-8837 .- 2211-8845. ; 12:1
  • Forskningsöversikt (refereegranskat)
Abstract Ämnesord
Stäng  
  • Background: Artificial Intelligence (AI) has great potential to transform health systems to improve the quality of healthcare services. However, AI is still new in Tanzania, and there is limited knowledge about the application of AI technology in the Tanzanian health sector.Objectives: This study aims to explore the current status, challenges, and opportunities for AI application in the health system in Tanzania. Methods: A scoping review was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis Extensions for Scoping Review (PRISMA-ScR). We searched different electronic databases such as PubMed, Embase, African Journal Online, and Google Scholar.Results: Eighteen (18) studies met the inclusion criteria out of 2,017 studies from different electronic databases and known AI-related project websites. Amongst AI-driven solutions, the studies mostly used machine learning (ML) and deep learning for various purposes, including prediction and diagnosis of diseases and vaccine stock optimisation. The most commonly used algorithms were conventional machine learning, including Random Forest and Neural network, Naive Bayes K-Nearest Neighbour and Logistic regression. Conclusions: This review shows that AI-based innovations may have a role in improving health service delivery, including early outbreak prediction and detection, disease diagnosis and treatment, and efficient management of healthcare resources in Tanzania. Our results indicate the need for developing national AI policies and regulatory frameworks for adopting responsible and ethical AI solutions in the health sector in accordance with the World Health Organisation (WHO) guidance on ethics and governance of AI for health.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)

Nyckelord

Artificial intelligence
Machine learning
Deep learning
Neural network
Health sector
Tanzania

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