ReviewJournal of clinical medicine2022
The Use of Artificial Intelligence Algorithms in the Diagnosis of Urinary Tract Infections-A Literature Review.
Review in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Machine learning models for early detection of urinary tract infections in kidney transplant patients.International urology and nephrology · 2026Article
- Rapid diagnostics innovations for urinary tract infections using molecular biology, artificial intelligence and antimicrobial resistance surveillance: a comprehensive review.Molecular biology reports · 2026Review
- Digital health interventions for urinary tract infection prevention and management in people living with dementia and their family caregivers: a scoping review.The Gerontologist · 2026Article
- Application of Machine Learning Algorithms in Urinary Tract Infections Diagnosis Based on Non-Microbiological Parameters.Pathogens (Basel, Switzerland) · 2025Article
- The Role of Artificial Intelligence in Urogynecology: Current Applications and Future Prospects.Diagnostics (Basel, Switzerland) · 2025Review
- Prediction of urinary tract infection using machine learning methods: a study for finding the most-informative variables.BMC medical informatics and decision making · 2025Article
- A personalized prediction model for distinguishing between asymptomatic bacteriuria and symptomatic urinary tract infections in patients with type 2 diabetes mellitus using machine learning.Frontiers in endocrinology · 2025Article
- A step forward in the diagnosis of urinary tract infections: from machine learning to clinical practice.Computational and structural biotechnology journal · 2024Article
- Artificial Intelligence (AI)-Based Detection of Anaemia Using the Clinical Appearance of the Gingiva.Cureus · 2024Article
- Electronic Phenotyping of Urinary Tract Infections as a Silver Standard Label for Machine Learning.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Artificial Intelligence Can Guide Antibiotic Choice in Recurrent UTIs and Become an Important Aid to Improve Antimicrobial Stewardship.Antibiotics (Basel, Switzerland) · 2023Article
- Clinical Decision Support systems: A step forward in establishing the clinical laboratory as a decision maker hubA CDS system protocol implementation in the clinical laboratory.Computational and structural biotechnology journal · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urinary tract infections (UTIs) are among the most common infections occurring across all age groups. UTIs are a well-known cause of acute morbidity and chronic medical conditions. The current diagnostic methods of UTIs remain sub-optimal. The development of better diagnostic tools for UTIs is essential for improving treatment and reducing morbidity. Artificial intelligence (AI) is defined as the science of computers where they have the ability to perform tasks commonly associated with intelligent beings. The objective of this study was to analyze current views regarding attempts to apply artificial intelligence techniques in everyday practice, as well as find promising methods to diagnose urinary tract infections in the most efficient ways. We included six research works comparing various AI models to predict UTI. The literature examined here confirms the relevance of AI models in UTI diagnosis, while it has not yet been established which model is preferable for infection prediction in adult patients. AI models achieve a high performance in retrospective studies, but further studies are required.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.