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Artificial Intelligence in Infectious Disease Clinical Practice: An Overview of Gaps, Opportunities, and Limitations
Author(s)
Andreas Sarantopoulos
Christina Mastori Kourmpani
Atshaya Lily Yokarasa
Chiedza Makamanzi
Polyna Antoniou
Nikolaos Spernovasilis
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.
Part Of
Tropical Medicine and Infectious Disease
Journal or Serie
Tropical Medicine and Infectious Disease
Issue
10
Volume
9
ISSN
24146366
Date Issued
2024-10
Open Access
Yes
DOI
10.3390/tropicalmed9100228
School
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
File(s)
No Thumbnail Available
Name
tropicalmed-09-00228-v2.pdf
Type
main article
Size
1.03 MB
Format
Checksum