PREDICTING TREATMENT UNFAVOURABLE IN PULMONARY TUBERCULOSIS PATIENTS USING STACKING ENSEMBLE MACHINE LEARNING APPROACH

PREDICTING TREATMENT UNFAVOURABLE IN PULMONARY TUBERCULOSIS PATIENTS USING STACKING ENSEMBLE MACHINE LEARNING APPROACH

The leading infectious disease-related cause of mortality for people is tuberculosis (TB). India is one of the countries with the highest rates of TB worldwide, making it a serious public health problem. People with active lung TB can spread the illness by spitting, coughing, or sneezing. In healt...

Full description

Saved in:
Bibliographic Details
Main Authors: Fayaz Ahamed Shaik, Lakshmanan Babu, Palaniyandi Paramasivam, Selvam Nagarajan, Sundarakumar Karuppasamy, Ponnuraja Chinnaiyan
Format: Article
Language:English
Published: Institute of Mechanics of Continua and Mathematical Sciences 2025-05-01
Series:Journal of Mechanics of Continua and Mathematical Sciences
Subjects:
clinical trial
cross-validation
ensemble
machine learning
pulmonary tuberculosis
Online Access:https://jmcms.s3.amazonaws.com/wp-content/uploads/2025/05/14184914/jmcms-2505003-Predicting-Treatment-Unfavorable-Shaik.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://jmcms.s3.amazonaws.com/wp-content/uploads/2025/05/14184914/jmcms-2505003-Predicting-Treatment-Unfavorable-Shaik.pdf

Similar Items