Research Article
Rural Area Health Care System: Disease Prediction with the Symptoms
@INPROCEEDINGS{10.4108/eai.28-4-2025.2357926, author={Uppara Sai Srinivas and M. Kameswara Rao and Vari Anitha and Venigalla Vaishnavi}, title={Rural Area Health Care System: Disease Prediction with the Symptoms }, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part I}, publisher={EAI}, proceedings_a={ICITSM PART I}, year={2025}, month={10}, keywords={rural health care system web-based platform offline support machine learning disease forecast / prediction symptom based input diagnostic tool}, doi={10.4108/eai.28-4-2025.2357926} }- Uppara Sai Srinivas
M. Kameswara Rao
Vari Anitha
Venigalla Vaishnavi
Year: 2025
Rural Area Health Care System: Disease Prediction with the Symptoms
ICITSM PART I
EAI
DOI: 10.4108/eai.28-4-2025.2357926
Abstract
Access to timely and accurate health services in rural areas is often limited due to the scarcity of medical professionals, lack of diagnostic tools and low health awareness. To address these challenges, this project presents a rural health system: web-based platform-based disease forecast that takes advantage of machine learning to help early detection of common diseases using symptom-based inputs. Currently, the system predicts five primary conditions: hypertension, diabetes, cold types, asthma and gastroenteritis, using appropriate algorithms such as random forest and logistics regression. Each model of disease is trained in relevant medical symptoms, allowing rapid and informative predictions without the need for medical experts. The platform is designed with simplicity and offline functionality in mind, the platform allows rural health professionals to enter the patient's symptoms and receive instant predictive feedback, reducing diagnostic time and workload. Additional planned resources include healthcare professional login to manage patient history, symptom tracking, medical suggestions and precautions, local accessibility translation and AI - powered chatbot for instant consultation resolution. These enhancements aim to make the system not only a diagnostic tool, but also a complete rural health management assistant, finally improving accessibility, awareness and results of medical care in needy regions.
