Authors : Dr. J. R. Nandwalkar; Aryan Kailash Bokde; Parth Avinash Adke; Riddhesh Sunil Jethe

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/5heaa3ss

Scribd : https://tinyurl.com/4rhmehuh

DOI : https://doi.org/10.38124/ijisrt/25apr1329

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Abstract : This research paper presents a web-based application titled “Doctor Appointment Booking and Handwriting Recognition System” designed to address two primary challenges in the healthcare sector: (1) simplifying the appointment booking process between patients and doctors, and (2) enabling the digital recognition of handwritten prescriptions. The platform is developed using the MERN stack (MongoDB, Express.js, React.js, Node.js) and integrates an OCR (Optical Character Recognition) module powered by deep learning techniques. The OCR module leverages a Convolutional Neural Network (CNN) trained on a combination of the EMNIST dataset and synthetic medical data to recognize individual characters in handwritten prescriptions. This character-level recognition is enhanced through modular development, offering a simpler yet effective solution for prescription digitization. The system supports user-friendly interaction, where patients can book appointments with doctors based on availability, and doctors have the autonomy to approve or decline requests. The admin dashboard enables global oversight of registration, approvals, and operational activities. This paper discusses the system architecture, implementation methodology, challenges faced, and potential enhancements for future scalability and accuracy.

Keywords : MERN, Doctor Appointment, OCR, Scheduling.

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