doi: 10.7763/IJCTE.2015.V7.957
Machine Learning: A Means of Diagnosing and Prescribing Treatments for Tuberculosis Patients
Arman James E. Avenir1
,
Jonas D. Villota2 ,
Maryli F. Rosas3
- 1Aegies People Support Center, Ayala Ave Cor. Gil Puyat Ave Makati City, Philippines.
- 2Blinkup Inc. 1404 Prime Land Tower, 2218 Market Street Madrigal Business Park Ayala Alabang, Muntinlupa City, Philippines.
- 3Computer Studies Department of De La Salle University – Dasmarinas, City of Dasmarinas Cavite, Philippines 4115.
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.
Keywords
- Diagnostic
- machine learning
- tuberculosis
- treatment
How to 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. https://doi.org/10.7763/IJCTE.2015.V7.957
Copyright & License
Copyright © 2015 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).