Sarantopoulos Andreas, Mastori Kourmpani Christina, Yokarasa Atshaya Lily, Makamanzi Chiedza, Antoniou Polyna, Spernovasilis Nikolaos, Tsioutis Constantinos
School of Medicine, European University of Cyprus, 2404 Nicosia, Cyprus.
Brigham Women's and Children Hospital, Boston, MA 02115, USA.
Trop Med Infect Dis. 2024 Sep 30;9(10):228. doi: 10.3390/tropicalmed9100228.
The integration of artificial intelligence (AI) in clinical medicine marks a revolutionary shift, enhancing diagnostic accuracy, therapeutic efficacy, and overall healthcare delivery. This review explores the current uses, benefits, limitations, and future applications of AI in infectious diseases, highlighting its specific applications in diagnostics, clinical decision making, and personalized medicine. The transformative potential of AI in infectious diseases is emphasized, addressing gaps in rapid and accurate disease diagnosis, surveillance, outbreak detection and management, and treatment optimization. Despite these advancements, significant limitations and challenges exist, including data privacy concerns, potential biases, and ethical dilemmas. The article underscores the need for stringent regulatory frameworks and inclusive databases to ensure equitable, ethical, and effective AI utilization in the field of clinical and laboratory infectious diseases.
人工智能（AI）在临床医学中的整合标志着一场革命性的转变，提高了诊断准确性、治疗效果和整体医疗服务水平。本综述探讨了AI在传染病领域的当前用途、益处、局限性及未来应用，重点介绍了其在诊断、临床决策和个性化医疗方面的具体应用。强调了AI在传染病领域的变革潜力，阐述了在快速准确的疾病诊断、监测、疫情检测与管理以及治疗优化方面存在的差距。尽管取得了这些进展，但仍存在重大局限性和挑战，包括数据隐私问题、潜在偏差和伦理困境。本文强调需要严格的监管框架和包容性数据库，以确保在临床和实验室传染病领域公平、合乎伦理且有效地利用AI。
