Smart Diagnosis of Urinary Tract Infections: is Artificial Intelligence the Fast-Lane Solution?
Naik N. Talyshinskii A. Shetty D.K. Hameed B.M.Z. Zhankina R. Somani B.K.
January 2024Springer
Current Urology Reports
2024#25Issue 137 - 47 pp.
Purpose of Review: Artificial intelligence (AI) can significantly improve physicians’ workflow when examining patients with UTI. However, most contemporary reviews are focused on examining the usage of AI with a restricted quantity of data, analyzing only a subset of AI algorithms, or performing narrative work without analyzing all dedicated studies. Given the preceding, the goal of this work was to conduct a mini-review to determine the current state of AI-based systems as a support in UTI diagnosis. Recent Findings: There are sufficient publications to comprehend the potential applications of artificial intelligence in the diagnosis of UTIs. Existing research in this field, in general, publishes performance metrics that are exemplary. However, upon closer inspection, many of the available publications are burdened with flaws associated with the improper use of artificial intelligence, such as the use of a small number of samples, their lack of heterogeneity, and the absence of external validation. AI-based models cannot be classified as full-fledged physician assistants in diagnosing UTIs due to the fact that these limitations and flaws represent only a portion of all potential obstacles. Instead, such studies should be evaluated as exploratory, with a focus on the importance of future work that complies with all rules governing the use of AI. Summary: AI algorithms have demonstrated their potential for UTI diagnosis. However, further studies utilizing large, heterogeneous, prospectively collected datasets, as well as external validations, are required to define the actual clinical workflow value of artificial intelligence.
Artificial intelligence , Diagnosis , Smart diagnosis , Tract infection , Urology
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Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India
Department of Urology, Astana Medical University, Astana, 010000, Kazakhstan
Department of Data Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India
Department of Urology, Father Muller Medical College, Karnataka, Mangalore, 575002, India
iTRUE-International Training and Research in Urology and Endourology, Karnataka, Manipal, 576104, India
Department of Urology, University Hospital Southampton NHS Trust, Southampton, SO16 6YD, United Kingdom
Department of Mechanical and Industrial Engineering
Department of Urology
Department of Data Science and Engineering
Department of Urology
iTRUE-International Training and Research in Urology and Endourology
Department of Urology
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