Year: 2025
Type: article
Abstract: Enhancing Rural Healthcare Accessibility Through AI-Driven Chatbots Abstract Rural healthcare faces numerous challenges, primarily stemming from limited access to medical resources and healthcare professionals. This research explores a novel approach to addressing these challenges by leveraging a web-based chatbot targeting rural communities. The chatbot is built using HTML, CSS, JavaScript, MySQL, Node.js, Python, and PHP, offering a comprehensive platform to assist individuals in identifying and addressing common health issues. Introduction The chatbot employs machine learning algorithms implemented in Python to analyze symptoms described by patients, facilitating the identification of potential ailments. Subsequently, the system provides users with information on their health concerns, recommends appropriate solutions, and suggests relevant medical practitioners. Functionality and Integration To bridge the gap between patients and healthcare providers, the chatbot further assists in scheduling appointments with local medical practitioners or government-provided hospitals. The system extends beyond medical advice, assisting in coordinating transportation and accommodation for patients, ensuring they can access healthcare facilities seamlessly. Keywords: Rural Healthcare, Chatbot, Telemedicine, Rural Health Services, General Physician, Digital Health.
DOI: 10.55041/ijsrem44104
Authors: Oweish Shaikh, Ronak Varia, Gaurav Kulkarni
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4409292522