Paper Details

Name: Vishesh Kaushik, Azhar Ashraf Gadoo, Ayush Jyoti & Vansh Bansal
Country: India

Year: 2026
Volume: Volume No: 13, January, Year: 2026 (Special Issue)
Page Number: 810-821
DOI: https://doi.org/10.5281/zenodo.19130489

ABSTRACT—
Artificial Intelligence has been one of the most vital innovations of the last decade. It has revolutionised our problemsolving ability by using powerful algorithms and different methods to achieve what was never done before. One field where artificial intelligence has provided us with major breakthroughs is healthcare. Primarily, the healthcare
system is very labour-intensive requiring doctors and nurses to work hard hours. Using artificial intelligence in disease diagnosis is one such use case where doctors can be helped and their burden lessened. Disease diagnosis is the most critical step in providing any patient with the care and medication they require. Sometimes diseases are not detected early and patients' health is compromised. Using tools like computer vision and algorithms like Random Forest, Logistic Regression can be used to effectively predict disease based on the patient‟s symptoms. In this paper we develop and web application solution which will have basic healthcare services like booking appointments with doctors, having one-to-one conversations with your healthcare professional and so on. This web app will also possess a feature of disease detection using machine learning algorithms. Logistic regression and the Random Forest algorithm have been used to implement the solution but the Support Vector Machine algorithm has also been used to compare results just by the developers. The paper starts with an introduction to the concept and provides an overview of the
system implemented. The next section provides a comprehensive literature summary of the previous work done in the field and how it began to start with. The subsequent section deals with the methods and insight into the technologies used to develop the web app and the fine details of machine learning algorithms. Lastly, results from the prediction of the implemented system are discussed and then future works to be taken up are discussed.

Keywords—Disease detection, Machine learning, logistic regression, healthcare