Using an Artificial Intelligence Approach to Predict the Adverse Effects and Prognosis of Tuberculosis
Journal
Diagnostics (Basel, Switzerland)
Journal Volume
13
Journal Issue
6
Pages
1075
Date Issued
2023-03-13
Author(s)
Abstract
Tuberculosis (TB) is one of the leading causes of death worldwide and a major cause of ill health. Without treatment, the mortality rate of TB is approximately 50%; with treatment, most patients with TB can be cured. However, anti-TB drug treatments may result in many adverse effects. Therefore, it is important to detect and predict these adverse effects early. Our study aimed to build models using an artificial intelligence/machine learning approach to predict acute hepatitis, acute respiratory failure, and mortality after TB treatment.
Subjects
acute hepatitis; artificial intelligence; machine learning; mortality; respiratory failure; tuberculosis
SDGs
Type
journal article