Fahim Yosri A, Hasani Ibrahim W, Kabba Samer, Ragab Waleed Mahmoud
Department of Basic Medical Sciences, Health Sector, Galala University, Suez, 43511, Egypt.
Faculty of Pharmacy, Al-Andalus University for Medical Sciences, Qadmus, Tartus, Syrian Arab Republic.
Eur J Med Res. 2025 Sep 23;30(1):848. doi: 10.1186/s40001-025-03196-w.
Healthcare systems worldwide face growing challenges, including rising costs, workforce shortages, and disparities in access and quality, particularly in low- and middle-income countries. Artificial intelligence (AI) has emerged as a transformative tool capable of addressing these issues by enhancing diagnostics, treatment planning, patient monitoring, and healthcare efficiency. AI's role in modern medicine spans disease detection, personalized care, drug discovery, predictive analytics, telemedicine, and wearable health technologies. Leveraging machine learning and deep learning, AI can analyze complex data sets, including electronic health records, medical imaging, and genomic profiles, to identify patterns, predict disease progression, and recommend optimized treatment strategies. AI also has the potential to promote equity by enabling cost-effective, resource-efficient solutions in low-resource and remote settings, such as mobile diagnostics, wearable biosensors, and lightweight algorithms. Successful deployment requires addressing critical challenges, including data privacy, algorithmic bias, model interpretability, regulatory oversight, and maintaining human clinical oversight. Emphasizing scalable, ethical, and evidence-driven implementation, key strategies include clinician training in AI literacy, adoption of resource efficient tools, global collaboration, and robust regulatory frameworks to ensure transparency, safety, and accountability. By complementing rather than replacing healthcare professionals, AI can reduce errors, optimize resources, improve patient outcomes, and expand access to quality care. This review emphasizes the responsible integration of AI as a powerful catalyst for innovation, sustainability, and equity in healthcare delivery worldwide.
全球医疗保健系统面临着日益严峻的挑战，包括成本上升、劳动力短缺以及医疗服务可及性和质量方面的差异，在低收入和中等收入国家尤为明显。人工智能（AI）已成为一种变革性工具，能够通过加强诊断、治疗规划、患者监测和提高医疗保健效率来解决这些问题。人工智能在现代医学中的作用涵盖疾病检测、个性化医疗、药物研发、预测分析、远程医疗和可穿戴健康技术。利用机器学习和深度学习，人工智能可以分析复杂的数据集，包括电子健康记录、医学影像和基因组图谱，以识别模式、预测疾病进展并推荐优化的治疗策略。人工智能还具有通过在资源匮乏和偏远地区提供具有成本效益、资源高效的解决方案来促进公平的潜力，例如移动诊断、可穿戴生物传感器和轻量级算法。成功部署需要应对关键挑战，包括数据隐私、算法偏差、模型可解释性、监管监督以及保持人类临床监督。强调可扩展、符合道德且以证据为驱动的实施，关键策略包括对临床医生进行人工智能素养培训、采用资源高效的工具、全球合作以及建立强大的监管框架，以确保透明度、安全性和问责制。通过补充而非取代医疗保健专业人员，人工智能可以减少错误、优化资源、改善患者预后并扩大优质医疗服务的可及性。本综述强调了负责任地整合人工智能，将其作为全球医疗保健服务创新、可持续性和公平性的强大催化剂。
