医疗人工智能技术在撒哈拉以南非洲的应用:医学实验室的前景

Q2 Health Professions
Richard Kobina Dadzie Ephraim , Gabriel Pezahso Kotam , Evans Duah , Frank Naku Ghartey , Evans Mantiri Mathebula , Tivani Phosa Mashamba-Thompson
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引用次数: 0

摘要

人工智能(AI)技术在全球范围内的广泛应用为各行各业带来了重大变革。人工智能辅助算法显著改善了决策、运营效率和生产力,尤其是在医疗保健和医药领域。然而,在中低收入国家(LMICs),尤其是撒哈拉以南非洲国家(SSA),医疗人工智能的整合面临着延误和挑战,减缓了其在医疗干预中的接受和实施。本专题叙述批判性地探讨了当前撒哈拉以南非洲应用医疗人工智能的趋势和模式,特别关注其对医学实验室的潜在影响。综述涵盖了医疗人工智能在撒哈拉以南非洲地区的一般使用情况,研究了影响医疗保健系统的推动因素、挑战和机遇等因素。此外,它还探讨了医疗人工智能对医学实验室的影响,并针对可能的整合提出了具体实用的建议。我们强调了各种挑战,包括数据可用性、安全问题、资源限制、监管漏洞、互联网连接不畅以及数字扫盲问题,这些都是导致人工智能在撒哈拉以南非洲地区医疗保健系统中整合缓慢的原因。尽管存在挑战,但在 SSA 医学实验室中采用医疗人工智能在提高诊断准确性、简化工作流程和加强患者护理方面仍具有潜在的潜力。要释放这些潜力,还需要进一步探索和仔细考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of medical artificial intelligence technology in sub-Saharan Africa: Prospects for medical laboratories

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.

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来源期刊
Smart Health
Smart Health Computer Science-Computer Science Applications
CiteScore
6.50
自引率
0.00%
发文量
81
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