Diagnosis of urinary tract infection based on artificial intelligence methods.
Journal:
Computer methods and programs in biomedicine
PMID:
30415718
Abstract
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflammation of other urinary tract organs. Since all of these infections have similar symptoms, it is difficult to identify the cause of primary infection. Therefore, it is not easy to diagnose a UTI with routine examination procedures. Invasive methods that require surgery could be necessary. This study aims to develop an artificial intelligence model to support the diagnosis of UTI with complex symptoms.
Authors
Keywords
Adolescent
Adult
Aged
Algorithms
Artificial Intelligence
Child
Cystitis
Decision Support Systems, Clinical
Decision Trees
Diagnosis, Computer-Assisted
False Positive Reactions
Female
Humans
Machine Learning
Male
Middle Aged
Neural Networks, Computer
ROC Curve
Sensitivity and Specificity
Support Vector Machine
Urinary Tract Infections
Young Adult