Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

ABSTRACT: Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physical examination, chest X-rays, and laboratory procedures, such as molecular testing and sputum culture. In artificial intelligence (AI), machine learning (ML) is an advanced study of statistical algorithms that can learn from historical data and generalize the results to unseen data. There are not many studies done on the ML algorithm that enables the prediction of treatment success for patients with pulmonary TB (PTB). The objective of this study is to identify an effective and predictive ML algorithm to evaluate the detection of treatment succ

SUBMITTER: Ahamed Fayaz S 

PROVIDER: S-EPMC11482692 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature