DocOnTap: AI-based disease diagnostic system and recommendation system
Zain ul Abideen, Talha Ali Khan, Raja Hashim Ali, Nisar Ali, Muhammad Muneeb Baig, Muhammad Ali
Abstract
In this age of technology, Artificial Intelligence plays a key part in humankind's growth, whether in education, daily life, or professional life. AI has improved how humans live and solve problems. Using illness mapping from symptoms, the suggested method recommends relevant doctors to users. The approach attempts to boost diagnosis efficiency, reducing misdiagnoses and saving doctors' time. Machine learning algorithms and doctors' diagnoses will reduce misdiagnosis. In this work, we built a disease-based prediction system with multiple machine learning algorithms including Decision Tree, Logistic Regression and Random Forest. We obtain the highest accuracy with Random Forest classifier. After diagnosis, our system will immediately schedule an appointment for them with the most conveniently located doctor in their area, and the system's evaluation will be delivered to the appointment doctor. The proposed system is accessible through website and both doctor and patient can use then for their purposes.