Prediction of Drug Resistance in Tuberculosis

Author(s)	Ms. Suravi H U, Ms. B Nayana, Mr. Bharath J Gowda, Mr. Nilesh Rajan, Supriya Suresh
Country	India
Abstract	Diagnosing drug-resistant Mycobacterium tuberculosis (MTB) currently takes 4–8 weeks, delaying treatment and putting patients at risk. Our solution uses machine learning to quickly analyze patient data—such as demographics, sputum tests, and GeneXpert results—to instantly predict resistance to key TB drugs like rifampicin. This rapid prediction helps doctors start the right treatment immediately, reducing delays, preventing disease progression, and improving patient outcomes.
Keywords	Clinical Decision Support, Drug Resistance, GeneXpert, Machine Learning Tuberculosis, Random Forest, SMOTE, Tuberculosis
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-27
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.46115
Short DOI	https://doi.org/g9mn5q

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International Journal For Multidisciplinary Research