provides a preliminary diagnosis for patients who could be suffering from the mosquito-borne diseases:
The Philippines, being a tropical country, is endemic to the said diseases. The continuously declining health services and the high disparity between the number of doctors and patients in the Philippines motivated the proponents of the study to develop such system.
The expert system is created by populating the knowledge base, then incorporating fuzzy logic with weighted rules.
The system is implemented with a human-machine interface which will prompt the user to the conventional check-up routine. The prototype is also integrated with a temperature sensor and electronic blood pressure monitor with built-in pulse rate sensor to record the user’s vital signs.
Testing of the algorithm was first done on simulated data provided by physicians.
It was then tested in Olongapo City General Hospital and Subic Family Care and Diagnostic Center. The system’s preliminarily diagnosis was compared with the expert’s diagnosis in a total of 80 tests with 20 tests per disease.
From the conducted tests, the system correctly pre-diagnosed:
Moreover, a chi-square test is also conducted; with a level of significance of 0.05 yielded a p-value of 0.464. Results show that the system can assess the patient to provide pre-diagnosis for the likelihood of dengue, chikungunya, and malaria. This is beneficial in the case of the inadequate proper medical attention given to patients in public hospitals—especially in rural areas.