Abstract:
Numerous developing nations, including Sri Lanka, struggle with healthcare challenges
stemming from insufficient personnel, a scarcity of modern medical equipment, and a
lack of contemporary hospitals in rural areas, contributing to elevated mortality rates in
remote regions. Addressing these issues, this paper proposes an innovative solution
through the development of an Android-based system. Specifically, a mobile expert
system has been designed and implemented to provide diagnoses for forty prevalent
diseases in Sri Lanka. The AI-powered Disease Prediction prototype provides early
illness detection during urgency. It employs symptom-based queries and can guess
possible illness when a person gets sick. For instance, if a person gets cough, he should
know some basic information related to the sickness and symptoms. If the cough is
mild, there is no need to go to doctor and waste money and time. Here, the person needs
to decide to meet a physician or not. This app enables users in this direction. The
mobile system utilizes Android operating system technology, which can be widely
adopted in Sri Lanka. Evaluation of the system involved user feedback, highlighting its
efficacy as a decision support tool for predicting and addressing common health issues
in the country. The Disease Prediction Android App, crafted using Android Studio,
exemplifies the application of Machine Learning in healthcare, enhancing disease
detection and prediction. This user-friendly app enables individuals to input symptoms
and facilitating early disease prediction. Leveraging the Naive Bayes algorithm, the
application swiftly and accurately identifies ailments based on user-provided
symptoms. In essence, this project underscores the potential of technology-driven
solutions to address healthcare challenges in developing nations, specifically in the
context of disease prediction.
