Abstract: According to Pakistan Medical and Dental Council (PMDC), Pakistan is facing a shortage of approximately 182,000 medical doctors. Due to the shortage of doctors; a large number of lives are in danger especially pregnant woman. A large number of pregnant women die every year due to pregnancy complications, and usually the reason behind their death is that the complications are not timely handled. In this paper, we proposed ontology-based clinical decision support system that diagnoses high-risk pregnant women and refer them to the qualified medical doctors for timely treatment. The Ontology of the proposed system is built automatically and enhanced afterward using doctor’s feedback. The proposed framework has been tested on a large number of test cases; experimental results are satisfactory and support the implementation of the solution.

Umar Manzoor, Muhammad Usman, Mohammed A. Balubaid and Ahmed Mueen, “Ontology-Based Clinical Decision Support System for Predicting High-Risk Pregnant Woman” International Journal of Advanced Computer Science and Applications(IJACSA), 6(12), 2015. http://dx.doi.org/10.14569/IJACSA.2015.061228

@article{Manzoor2015,
title = {Ontology-Based Clinical Decision Support System for Predicting High-Risk Pregnant Woman},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.061228},
url = {http://dx.doi.org/10.14569/IJACSA.2015.061228},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {12},
author = {Umar Manzoor and Muhammad Usman and Mohammed A. Balubaid and Ahmed Mueen}
}