[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118913-en":3,"doc-seo-118913-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118913,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1782875107921204101",6,"Technology","Exploring the matrix - knowledge, perceptions and prospects of artificial intelligence and machine learning in Nigerian healthcare","Study assessing Nigerian healthcare professionals’ knowledge and perceptions of artificial intelligence (AI) and machine learning (ML) application in healthcare. A cross-sectional questionnaire-based survey was conducted across Nigeria’s six geopolitical zones using stratified multistage sampling, followed by descriptive and inferential statistical analyses. Results show a majority with good AI/ML knowledge, mixed views on job-loss concerns, and broad support for AI integration to augment human intelligence and improve service efficiency. Findings inform policymakers on deployment decisions.","TYPE Original Research PUBLISHED 19 January 2024 DOI 10. 3389/frai.2023.1293297  \nOPEN ACCESS  \nEDITED BY  \nKathiravan Srinivasan,  \nVellore Institute of Technology, Vellore, India  \nREVIEWED BY  \nFarkhondeh Asadi,  \nHealth Information Management, Machine Learning Application in Healthcare, Medical  \nInformatics, Iran Ana Guerrero-Tamayo, University of Deusto, Spain Rakesh Chandra Joshi,  \nDr. A. P.J. Abdul Kalam Technical University, India  \n*CORRESPONDENCE  \nObi Peter Adigwe  \n [o.p.adigwe@niprd.gov.ng](o.p.adigwe@niprd.gov.ng)[ ](o.p.adigwe@niprd.gov.ng)Godspower Onavbavba  \n [onavbavbagodspower@gmail.com](onavbavbagodspower@gmail.com)  \nRECEIVED 12 September 2023  \nACCEPTED 21 November 2023  \nPUBLISHED 19 January 2024  \nCITATION  \nAdigwe OP, Onavbavba G and Sanyaolu SE (2024) Exploring the matrix: knowledge, perceptions and prospects of artificial intelligence and machine learning in Nigerian healthcare. Front. Artif. Intell. 6:1293297 .  \ndoi: 10.3389/frai.2023.1293297  \nCOPYRIGHT  \n© 2024 Adigwe, Onavbavba and Sanyaolu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nExploring the matrix: knowledge, perceptions and prospects of artificial intelligence and machine learning in Nigerian healthcare  \nObi Peter Adigwe*, Godspower Onavbavba* and Saheed Ekundayo Sanyaolu  \nNational Institute for Pharmaceutical Research and Development, Abuja, Nigeria  \nBackground: Artificial intelligence technology can be applied in several aspects of healthcare delivery and its integration into the Nigerian healthcare value chain is expected to bring about new opportunities. This study aimed at assessing the knowledge and perception of healthcare professionals in Nigeria regarding the application of artificial intelligence and machine learning in the health sector.  \nMethods: A cross-sectional study was undertaken amongst healthcare professionals in Nigeria with the use of a questionnaire. Data were collected across the six geopolitical zones in the Country using a stratified multistage sampling method. Descriptive and inferential statistical analyses were undertaken for the data obtained.  \nResults: Female participants (55 . 7%) were slightly higher in proportion compared to the male respondents (44 . 3%) . Pharmacists accounted for 27 . 7% of the participants, and this was closely followed by medical doctors (24 . 5%) and nurses (19 . 3%) . The majority of the respondents (57 . 2%) reported good knowledge regarding artificial intelligence and machine learning, about a third of the participants (32 . 2%) were of average knowledge, and 10 .6% of the sample had poor knowledge. More than half of the respondents (57 .8%) disagreed with the notion that the adoption of artificial intelligence in the Nigerian healthcare sector could result in job losses. Two-thirds of the participants (66 . 7%) were of the view that the integration of artificial intelligence in healthcare will augment human intelligence. Three-quarters (77%) of the respondents agreed that the use of machine learning in Nigerian healthcare could facilitate e􀀈cient service delivery.  \nConclusion: This study provides novel insights regarding healthcare professionals’knowledge and perception with respect to the application of artificial intelligence and machine learning in healthcare. The emergent findings from this study can guide government and policymakers in decision-making as regards deployment of artificial intelligence and machine learning for healthcare delivery.  \nKEYWORDS  \nartificial intelligence (AI), machine learning (ML), algorithms, clinical decision-making, healthcare  \nBackground  \nArt","cbCaiuvKWTjhzuV0","https://ap.wps.com/l/cbCaiuvKWTjhzuV0","pdf",849758,1,10,"English","en",105,"# Background\n## Artificial intelligence\n## Machine learning\n# Methods\n## Study design and sampling\n# Results\n## Participants’ knowledge levels\n## Perceptions on job loss and intelligence augmentation\n## Machine learning and service delivery\n# Conclusion","[{\"question\":\"What was the main objective of the study on AI and ML in Nigerian healthcare?\",\"answer\":\"The study aimed to assess healthcare professionals’ knowledge and perceptions regarding AI and ML application in Nigeria’s health sector.\"},{\"question\":\"How was the survey conducted and what sampling method was used?\",\"answer\":\"A cross-sectional questionnaire survey was conducted among healthcare professionals across Nigeria’s six geopolitical zones using stratified multistage sampling, followed by descriptive and inferential statistics.\"},{\"question\":\"What did the results show about participants’ knowledge of AI and machine learning?\",\"answer\":\"Most respondents reported good knowledge, about a third had average knowledge, and a smaller portion reported poor knowledge.\"}]","Exploring the matrix - 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