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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42822
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In today’s fast-paced world, accessing timely medical care can be challenging due to long wait times, scheduling difficulties, and a lack of proper guidance. The Doctor Appointment System addresses these issues by integrating AI and machine learning to create a more efficient and accessible healthcare experience. It ensures secure access with OTP-based authentication, preventing unauthorized logins. A machine learning-powered disease prediction model helps patients analyze symptoms and gain preliminary insights before consulting a doctor, while an AI-driven chatbot provides instant assistance, answering queries and guiding users through the appointment process. To enhance convenience, the system includes a Nearby Hospital Locator, allowing users to search for hospitals based on their city. An admin-controlled scheduling system manages appointments efficiently, enabling administrators to approve or reject requests based on doctor availability while maintaining a specialist patient limit to avoid overbooking. Additionally, a feedback system allows users to report issues and provide input for continuous improvements. By integrating secure authentication, AI-driven assistance, predictive analytics, and location-based hospital search, this system enhances accessibility, reduces waiting times, and ensures a smooth and organized appointment booking process for both patients and healthcare providers.
KEYWORDS
Publication Date
3/22/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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