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Review
. 2024 Sep 30;9(10):228.
doi: 10.3390/tropicalmed9100228.

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

Andreas Sarantopoulos  1   2 , Christina Mastori Kourmpani  1 , Atshaya Lily Yokarasa  1 , Chiedza Makamanzi  1 , Polyna Antoniou  1 , Nikolaos Spernovasilis  3   4 , Constantinos Tsioutis  1
Affiliations
Review

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

Andreas Sarantopoulos et al. Trop Med Infect Dis. .

Abstract

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.

Keywords: artificial intelligence; clinical medicine; data privacy; deep learning; diagnosis; ethics; limitations; machine learning; personalized medicine; research; therapeutics.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Functions of artificial intelligence.
Figure 2
Figure 2
Current applications of AI in clinical infectious diseases.
See this image and copyright information in PMC

References

    1. Amisha, Malik P., Pathania M., Rathaur V.K. Overview of Artificial Intelligence in Medicine. J. Fam. Med. Prim. Care. 2019;8:2328–2331. doi: 10.4103/jfmpc.jfmpc_440_19. - DOI - PMC - PubMed
    1. Krishnan G., Singh S., Pathania M., Gosavi S., Abhishek S., Parchani A., Dhar M. Artificial Intelligence in Clinical Medicine: Catalyzing a Sustainable Global Healthcare Paradigm. Front. Artif. Intell. 2023;6:1227091. doi: 10.3389/frai.2023.1227091. - DOI - PMC - PubMed
    1. Hamet P., Tremblay J. Artificial Intelligence in Medicine. Metab. Clin. Exp. 2017;69:S36–S40. doi: 10.1016/j.metabol.2017.01.011. - DOI - PubMed
    1. Pettit R.W., Fullem R., Cheng C., Amos C.I. Artificial Intelligence, Machine Learning, and Deep Learning for Clinical Outcome Prediction. Emerg. Top. Life Sci. 2021;5:729–745. doi: 10.1042/ETLS20210246. - DOI - PMC - PubMed
    1. Sarker I.H. Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions. SN Comput. Sci. 2021;2:420. doi: 10.1007/s42979-021-00815-1. - DOI - PMC - PubMed