Hudu Shuaibu Abdullahi, Alshrari Ahmed Subeh, Abu-Shoura Esra'a Jebreel Ibrahim, Osman Amira, Jimoh Abdulgafar Olayiwola
Department of Basic and Clinical Medical Sciences, Faculty of Dentistry, Zarqa University, Zarqa 13110, Jordan.
Department of Medical Laboratory Technology, Faculty of Applied Medical Science, Northern Border University, Arar 91431, Saudi Arabia.
Interdiscip Perspect Infect Dis. 2025 Mar 6;2025:6816002. doi: 10.1155/ipid/6816002. eCollection 2025.
This paper explores the transformative potential of integrating artificial intelligence (AI) in the diagnosis and prognosis of infectious diseases. By analyzing diverse datasets, including clinical symptoms, laboratory results, and imaging data, AI algorithms can significantly enhance early detection and personalized treatment strategies. This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. It also addresses the challenges and ethical considerations associated with AI, including data privacy, algorithmic bias, and equitable access to healthcare. Highlighting case studies and recent advancements, the paper underscores AI's role in revolutionizing infectious disease management and its implications for future healthcare delivery.
本文探讨了将人工智能(AI)整合到传染病诊断和预后中的变革潜力。通过分析包括临床症状、实验室结果和影像数据在内的各种数据集,人工智能算法可以显著提高早期检测和个性化治疗策略。本文综述了人工智能驱动的模型如何提高诊断准确性、预测患者预后以及对有效的疾病管理做出贡献。它还讨论了与人工智能相关的挑战和伦理考量,包括数据隐私、算法偏差以及医疗保健的公平获取。通过突出案例研究和最新进展,本文强调了人工智能在彻底改变传染病管理方面的作用及其对未来医疗服务的影响。