[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2334":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"view_count":15,"doi":24,"paper":25,"created_at":43},2334,"Role of Artificial Intelligence in Addressing Major Healthcare Access Challenges across Africa","https:\u002F\u002Fdoi.org\u002F10.65757\u002Fhjhpd.41","Access to healthcare continues to be a major hurdle in many African countries, primarily due to insufficient medical infrastructure, a lack of healthcare professionals, limited services in rural areas, high disease prevalence, and ineffective health information management systems. This survey explores how artificial intelligence (AI) can address these issues and enhance the quality of healthcare delivery throughout Africa. This study aims to identify key problems related to healthcare access, evaluate current AI-driven healthcare solutions, and measure their effectiveness in improving health outcomes. It utilizes a thorough review and analysis of literature, case studies, industry reports, and documented AI healthcare implementations across various African nations. The findings reveal that AI technologies, including machine learning, deep learning, predictive analytics, telemedicine platforms, clinical decision support systems, and intelligent health chatbots, have made significant strides in areas such as disease diagnosis, remote healthcare delivery, epidemic surveillance, patient monitoring, and healthcare resource management. Additionally, AI has shown great promise in lowering healthcare costs, enhancing diagnostic accuracy, and expanding services to underserved communities. However, challenges such as poor digital infrastructure, data privacy issues, limited funding, regulatory hurdles, and a shortage of AI expertise still pose significant barriers to widespread adoption. The study concludes that strategic investments, supportive policies, and capacity-building initiatives are crucial for unlocking the transformative potential of AI in improving healthcare accessibility and sustainability across Africa.","在许多非洲国家，获得医疗服务仍然是一大障碍，主要原因包括医疗基础设施不足、医护人员短缺、农村地区服务有限、疾病流行率高以及健康信息管理系统效率低下。本综述探讨了人工智能（AI）如何解决这些问题并提升整个非洲的医疗服务交付质量。本研究旨在识别与医疗服务获取相关的关键问题，评估当前由AI驱动的医疗解决方案，并衡量其在改善健康结果方面的有效性。研究采用了对文献、案例研究、行业报告以及非洲各国已记录的AI医疗实施情况的全面回顾与分析。研究结果表明，包括机器学习、深度学习、预测分析、远程医疗平台、临床决策支持系统和智能健康聊天机器人在内的AI技术，已在疾病诊断、远程医疗服务、疫情监测、患者监测和医疗资源管理等领域取得了显著进展。此外，AI在降低医疗成本、提高诊断准确性和将服务扩展至欠发达社区方面展现出巨大潜力。然而，数字基础设施薄弱、数据隐私问题、资金有限、监管障碍以及AI专业人才短缺等挑战，仍然对AI的广泛采用构成重大阻碍。研究得出结论，战略投资、支持性政策和能力建设举措对于释放AI在改善非洲医疗服务可及性和可持续性方面的变革潜力至关重要。",null,"Hensard Journal of Health Governance and Digital Transformation","2026-09-10T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"主题为非洲医疗可及性与AI应用，与三农、农业信息化、智慧农业无关，不通过相关性门槛。",[19],{"name":10,"url":6},[21,22,23],"农业人工智能","数字鸿沟","智慧医疗","10.65757\u002Fhjhpd.41",{"doi":24,"openalex_id":26,"authors":27,"venue":10,"cited_by_count":15,"oa_url":34,"card":35,"direction":41,"ingested_from":42},"W7212114055",[28,30,32],{"name":29,"orcid":9},"Ibikunle Frank Ayoleke",{"name":31,"orcid":9},"Shammah Ndubuisi",{"name":33,"orcid":9},"Francis Smith Correct","https:\u002F\u002Fhensardjournals.com\u002Findex.php\u002FHJHG\u002Farticle\u002Fdownload\u002F72\u002F87",{"tldr":36,"method":37,"finding":38,"direction":39,"opportunity":40},"综述AI在非洲医疗可及性挑战中的应用、成效与障碍。","文献综述、案例与行业报告分析多国AI医疗落地。","AI在诊断、远程医疗和资源管理上有效，但基建、隐私和人才仍是主要障碍。","其他","可探索面向低资源农村的轻量级AI分诊与离线远程医疗方案，并评估其可持续性。","数字乡村与农业信息化","openalex","2026-09-13T23:30:34.007463Z"]