Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2024 Dec;56(1):2362869.
doi: 10.1080/07853890.2024.2362869. Epub 2024 Jun 10.

Machine learning in infectious diseases: potential applications and limitations

Ahmad Z Al Meslamani  1   2 , Isidro Sobrino  3 , José de la Fuente  3   4
Affiliations
Review

Machine learning in infectious diseases: potential applications and limitations

Ahmad Z Al Meslamani et al. Ann Med. 2024 Dec.

Abstract

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. It explores challenges in key areas such as outbreak prediction, pathogen identification, drug discovery, and personalized medicine. We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.

Keywords: Artificial intelligence; Big Data; infectious diseases; machine learning; vaccine.

Plain language summary

Infectious diseases are a major challenge worldwideArtificial Intelligence (AI) combined algorithms have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseasesFuture directions include applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases.

PubMed Disclaimer

Conflict of interest statement

The author J. de la Fuente is section editor in the same journal. We declare no other competing interests.

Figures

Figure 1.
Figure 1.
Challenges to ML in infectious diseases and potential approaches and applications.
See this image and copyright information in PMC

References

    1. Al Meslamani AZ, Jarab AS, Ghattas MA.. The role of machine learning in healthcare responses to pandemics: maximizing benefits and filling gaps. J Med Econ. 2023;26(1):1–10. doi: 10.1080/13696998.2023.2224018. - DOI - PubMed
    1. Abou Hajal A, Al Meslamani AZ.. Overcoming barriers to machine learning applications in toxicity prediction. Expert Opin Drug Metab Toxicol. 2023:1–5. doi: 10.1080/17425255.2023.2294939. - DOI - PubMed
    1. Park DJ, Park MW, Lee H, et al. Development of machine learning model for diagnostic disease prediction based on laboratory tests. Sci Rep. 2021;11(1):7567. doi: 10.1038/s41598-021-87171-5. - DOI - PMC - PubMed
    1. Zoabi Y, Kehat O, Lahav D, et al. Predicting bloodstream infection outcome using machine learning. Sci Rep. 2021;11(1):20101. doi: 10.1038/s41598-021-99105-2. - DOI - PMC - PubMed
    1. Peiffer-Smadja N, Rawson TM, Ahmad R, et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect. 2020;26(8):1118. doi: 10.1016/j.cmi.2019.09.009. - DOI - PubMed