Artificial Intelligence in Infectious Disease Clinical Practice: An Overview of Gaps, Opportunities, and Limitations

被引:2
|
作者
Sarantopoulos, Andreas [1 ,2 ]
Kourmpani, Christina Mastori [1 ]
Yokarasa, Atshaya Lily [1 ]
Makamanzi, Chiedza [1 ]
Antoniou, Polyna [1 ]
Spernovasilis, Nikolaos [3 ,4 ]
Tsioutis, Constantinos [1 ]
机构
[1] European Univ Cyprus, Sch Med, CY-2404 Nicosia, Cyprus
[2] Brigham Womens & Children Hosp, Boston, MA 02115 USA
[3] German Oncol Ctr, Dept Infect Dis, CY-4108 Limassol, Cyprus
[4] Univ Crete, Sch Med, Iraklion 71110, Greece
关键词
artificial intelligence; clinical medicine; data privacy; deep learning; diagnosis; ethics; limitations; machine learning; personalized medicine; research; therapeutics;
D O I
10.3390/tropicalmed9100228
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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.
引用
收藏
页数:12
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