AI-enhanced healthcare management during natural disasters: conceptual insights

Samira Abdul, Ehizogie Paul Adeghe, Bisola Oluwafadekemi Adegoke, Adebukola Adejumoke Adegoke, Emem Henry Udedeh
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Abstract

Natural disasters often lead to significant disruptions in healthcare delivery, exacerbating the already formidable challenges faced by healthcare systems. Leveraging artificial intelligence (AI) offers a promising approach to mitigate these challenges and enhance healthcare management during and after natural disasters. This conceptual paper aims to propose a framework for the integration of AI into disaster response efforts, with a focus on optimizing resource allocation, improving patient triage, and enhancing overall system resilience.  Through a comprehensive review of existing literature, this paper identifies the gaps in current disaster management practices and explores the potential of AI to address these shortcomings. By analyzing case studies and examples from previous disasters, the paper highlights the transformative impact that AI technologies such as predictive analytics, machine learning, and robotics can have on healthcare delivery in crisis situations. The objectives of this paper are twofold: to define a strategic approach for incorporating AI into disaster response protocols and to outline the expected outcomes of implementing such a framework. Expected benefits include expedited triage processes, more accurate resource allocation, and improved communication systems, ultimately leading to better patient outcomes and enhanced system efficiency. The proposed framework emphasizes the importance of interdisciplinary collaboration between healthcare professionals, technologists, policymakers, and disaster response experts. It also addresses ethical considerations and potential challenges associated with AI implementation in disaster settings. In conclusion, this paper underscores the critical role of AI in bolstering healthcare management capabilities during natural disasters. By leveraging AI technologies, healthcare systems can become more adaptive, responsive, and resilient in the face of unforeseen challenges, ultimately saving lives and minimizing the impact of disasters on communities. Keywords: AI-Enhanced Healthcare Management, Natural Disasters, Conceptual Insights.
自然灾害期间的人工智能强化医疗管理:概念见解
自然灾害往往会导致医疗服务严重中断,加剧医疗系统本已面临的严峻挑战。利用人工智能(AI)为减轻这些挑战并加强自然灾害期间和灾后的医疗保健管理提供了一种前景广阔的方法。这篇概念性论文旨在提出一个将人工智能融入灾害响应工作的框架,重点是优化资源分配、改善患者分流和提高整个系统的复原力。 通过对现有文献的全面回顾,本文找出了当前灾害管理实践中的不足,并探讨了人工智能解决这些不足的潜力。通过分析以往灾难中的案例研究和实例,本文强调了预测分析、机器学习和机器人等人工智能技术对危机情况下的医疗服务所能产生的变革性影响。本文的目标有两个:确定将人工智能纳入灾难响应协议的战略方法,并概述实施这种框架的预期结果。预期的好处包括加快分诊流程、更准确地分配资源和改进通信系统,最终改善患者的治疗效果并提高系统效率。建议的框架强调了医疗保健专业人员、技术专家、决策者和灾难应对专家之间跨学科合作的重要性。本文还探讨了与在灾难环境中实施人工智能相关的伦理考虑因素和潜在挑战。总之,本文强调了人工智能在加强自然灾害期间医疗保健管理能力方面的关键作用。通过利用人工智能技术,医疗保健系统在面对不可预见的挑战时可以变得更具适应性、响应性和复原力,最终挽救生命并最大限度地减少灾害对社区的影响。关键词人工智能增强医疗保健管理 自然灾害 概念性启示
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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