Pet dog disease pre-diagnosis system for caregiver with possibilistic C-means clustering and disease database - Kwang Baek Kim; Doo Heon Song (Indonesian Journal of Electrical Engineering and Computer Science, 2020)
While the population of pet dogs and veterinary clinics are increasing, there is no reliable and useful software for pet owners/caregivers who have limited knowledge on the pet diseases. In this paper, we propose a pre-diagnosis system working on the mobile platform that the pet owner can take a pre-diagnosis from his/her observation of pet dog’s abnormality. Technically, the system needs a reliable databases for disease-symptom association thus we provide it based on the textbook and encyclopedia. Then, we apply Possibilistic C-Means algorithm that is an unsupervised machine learning algorithm to form the connections between disease and symptoms from database. The system outputs five most probable diseases from the observed symptoms of pet dog. The utility of this system is to alert the owner’s attention on the pet dog’s abnormal behavior and try to find the diseases as soon as possible.