Richard Kobina Dadzie Ephraim , Gabriel Pezahso Kotam , Evans Duah , Frank Naku Ghartey , Evans Mantiri Mathebula , Tivani Phosa Mashamba-Thompson
{"title":"Application of medical artificial intelligence technology in sub-Saharan Africa: Prospects for medical laboratories","authors":"Richard Kobina Dadzie Ephraim , Gabriel Pezahso Kotam , Evans Duah , Frank Naku Ghartey , Evans Mantiri Mathebula , Tivani Phosa Mashamba-Thompson","doi":"10.1016/j.smhl.2024.100505","DOIUrl":null,"url":null,"abstract":"<div><p>The widespread adoption of artificial intelligence (AI) technology globally has brought significant changes to various sectors. AI-assisted algorithms have notably improved decision-making, operational efficiency, and productivity, especially in healthcare and medicine. However, in low and middle-income countries (LMICs), particularly in sub-Saharan Africa (SSA), the integration of medical AI has faced delays and challenges, slowing its acceptance and implementation in medical interventions. This thematic narrative critically explores the current trends and patterns in applying medical AI in SSA, with a specific focus on its potential impact on medical laboratories. The review covers the general use of medical AI in SSA, examining factors like enablers, challenges, and opportunities that influence healthcare systems. Additionally, it looks into the implications of medical AI for medical laboratories and suggests context-specific and practical recommendations for potential integration. We highlight various challenges, including data availability, security concerns, resource limitations, regulatory gaps, poor internet connectivity, and digital literacy issues, contributing to the slow integration of AI in healthcare systems in SSA. Despite challenges, the adoption of medical AI in SSA medical laboratories holds latent potential for improving diagnostic accuracy, streamlining workflows, and enhancing patient care. Further exploration and careful consideration are necessary to unlock these possibilities.</p></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"33 ","pages":"Article 100505"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352648324000618/pdfft?md5=5ebc9f63c766918d348d9c6ec4b33b87&pid=1-s2.0-S2352648324000618-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352648324000618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
The widespread adoption of artificial intelligence (AI) technology globally has brought significant changes to various sectors. AI-assisted algorithms have notably improved decision-making, operational efficiency, and productivity, especially in healthcare and medicine. However, in low and middle-income countries (LMICs), particularly in sub-Saharan Africa (SSA), the integration of medical AI has faced delays and challenges, slowing its acceptance and implementation in medical interventions. This thematic narrative critically explores the current trends and patterns in applying medical AI in SSA, with a specific focus on its potential impact on medical laboratories. The review covers the general use of medical AI in SSA, examining factors like enablers, challenges, and opportunities that influence healthcare systems. Additionally, it looks into the implications of medical AI for medical laboratories and suggests context-specific and practical recommendations for potential integration. We highlight various challenges, including data availability, security concerns, resource limitations, regulatory gaps, poor internet connectivity, and digital literacy issues, contributing to the slow integration of AI in healthcare systems in SSA. Despite challenges, the adoption of medical AI in SSA medical laboratories holds latent potential for improving diagnostic accuracy, streamlining workflows, and enhancing patient care. Further exploration and careful consideration are necessary to unlock these possibilities.