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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2015 Vol.7(3): 201-206 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.957

Machine Learning: A Means of Diagnosing and Prescribing Treatments for Tuberculosis Patients

Arman James E. Avenir, Jonas D. Villota, and Maryli F. Rosas
Abstract—Tuberculosis (TB) remains one of the leading health problems in the Philippines. Although curable, many Filipinos cannot afford the cost of treatment. Furthermore, the free services offered by the public health centers are insufficient to attend to the medical needs of those seeking help. In this paper, the researchers present the system that can assist doctors, nurses and health workers in diagnosing tuberculosis using techniques in machine learning through applying ID3 algorithm. Interviews with several experts in the field of TB were conducted in order to gather data that were used to populate the system’s knowledge base. Test result show that the system is capable of prescribing treatments based on the patient’s data and tracking the progress of the patient based on his/her prescribed treatment.

Index Terms—Diagnostic, machine learning, tuberculosis, treatment.

Arman James E. Avenir is with Aegies People Support Center, Ayala Ave Cor. Gil Puyat Ave Makati City, Philippines (e-mail: armanavenir@gmail.com).
Jonas D. Villota is with Blinkup Inc. 1404 Prime Land Tower, 2218 Market Street Madrigal Business Park Ayala Alabang, Muntinlupa City, Philippines (e-mail: jonsader.14@yahoo.com).
Maryli F. Rosas is with the Computer Studies Department of De La Salle University – Dasmarinas, City of Dasmarinas Cavite, Philippines 4115 (e-mail: ilyramrosas@yahoo.com).


Cite:Arman James E. Avenir, Jonas D. Villota, and Maryli F. Rosas, "Machine Learning: A Means of Diagnosing and Prescribing Treatments for Tuberculosis Patients," International Journal of Computer Theory and Engineering vol. 7, no. 3, pp. 201-206, 2015.

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