International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Based Doctor Appointment Scheduling and Disease Diagnosis |
|---|---|
| ABSTRACT | Access to healthcare remains a critical challenge across rural and semi-urban regions of India, where patients encounter difficulties such as limited availability of specialist doctors, communication barriers due to regional language diversity, absence of early screening tools, and fragmented systems for booking medical consultations. These issues often lead to delayed treatment, worsened health outcomes, and unnecessary travel to distant urban hospitals. Swasth AI addresses these challenges through an intelligent healthcare platform that enables users to describe symptoms via text or voice in seven Indian languages, receive AI-powered preliminary health assessments, identify suitable doctors through a multi-factor ranking system, and book appointments with automated email confirmations. Additionally, the platform incorporates a deep learning module for image-based skin condition classification using a Convolutional Neural Network trained on clinical dermatology data. The system architecture employs React 19 with Next.js 15 for the user interface, a Python-based REST API with PostgreSQL for data management, TensorFlow.js for in-browser model inference, the Web Speech API for multilingual voice recognition, and EmailJS for patient notifications. A geolocation-powered hospital mapping feature helps users identify nearby healthcare facilities without reliance on external map services. By combining NLP-driven symptom analysis, transfer learning for medical image classification, intelligent scheduling with patient registration, and an emergency alert mechanism, SwasthAI delivers an accessible, technology-driven healthcare experience designed to serve communities with limited medical infrastructure. |
| AUTHOR | PAVITHRA MADIPEDDI, G. NARASIMHAM Post Graduate Student, Department of Computer Science and Engineering (Data Science), Jawaharlal Nehru Technological University, Hyderabad, India Associate Professor, Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, India |
| VOLUME | 185 |
| DOI | DOI: 10.15680/IJIRCCE.2026.14060109 |
| pdf/109_AI-Based Doctor Appointment Scheduling and Disease Diagnosis.pdf | |
| KEYWORDS | |
| References | [1] "Next.js – The React Framework for the Web," Vercel.Available: https://nextjs.org/ [2] "TensorFlow.js – Machine Learning for JavaScript," Google. Available: https://www.tensorflow.org/js [3] "Web Speech API – Speech Recognition," MDN Web Docs. Available: https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API [4] "EmailJS – Send Emails Directly from JavaScript," EmailJS. Available: https://www.emailjs.com/ [5] PostgreSQL Global Development Group, "PostgreSQL: Open-Source Relational Database System,"Version 16, 2024. Available: https://www.postgresql.org/ [6] "TailwindCSS – A Utility-First CSS Framework." Available: https://tailwindcss.com/ [7] "React – A JavaScript Library for Building User Interfaces," Meta Platforms.Available: https://react.dev/ |
