 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: April 2025
Volume 10 | Issue 4
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 107
Article Submitted : 14255
Article Published : 6531
Total Authors : 17369
Total Reviewer : 639
Total Countries : 118
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AI-Driven Doctor Scheduling for Efficient Patient Appointments |
| Authors Name: | Jai Hardas , Omkar Shelke , Atul Rathod , Nilesh Mohite , Prof. Smruti S. Barik |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200713
|
| Published Paper Id: | IJRTI2502066 |
| Published In: | Volume 10 Issue 2, February-2025 |
| DOI: | |
| Abstract: | This paper presents an AI-enhanced Doc- tor Appointment System designed to optimize the scheduling of medical appointments. The system is composed of four main modules: Patient, Hospital Administration, Doctor, and Admin. Upon logging in, users can input their location and symptoms, enabling the system to suggest nearby hospitals based on distance and ratings. Patients can then choose specialist doctors from comprehensive profiles and reviews. Doctors have the capability to update their availability, while hospital administrators can manage appointments for walk-in patients. The system also includes features for notifications and cancellation alerts to improve the user experience. The primary goal of this system is to enhance patient satisfaction, optimize hospital resource usage, and increase the efficiency of medical services. By integrating AI components, the system aims to refine scheduling processes, reduce congestion, and offer a smooth user experience. It utilizes a machine learning model based on Support Vector Machines (SVM) to predict appointment attendance. In today’s fast-paced environment, reliable healthcare services are essential. This approach attempts to improve the connection between patients and healthcare providers by implementing a practical and user-friendly system. Furthermore, the technology provides medical personnel with a powerful tool for effectively managing their calendars, reducing administrative work and assuring a great patient experience. AI-powered doctor appointment system, medical schedule optimization, patient happiness, hospital administration, doctor availability management, location-based hospital search, special- ized doctor referral, notification system, cancelation alerts, and healthcare efficiency. |
| Keywords: | The Doctor Appointment System leverages AI technology to streamline the process of scheduling medical appointments. This system is structured into four main modules: Patient, Hospital Administration, Doctor, and Admin. Key fea- tures include: patient satisfaction, hospital administration, doctor scheduling, location-based hospital search, specialist doctor rec- ommendation, notification system, cancellation alerts, healthcare efficiency. |
| Cite Article: | "AI-Driven Doctor Scheduling for Efficient Patient Appointments", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 2, page no.a640-a643, February-2025, Available :http://www.ijrti.org/papers/IJRTI2502066.pdf |
| Downloads: | 00092 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2502066
Registration ID:200713
Published In: Volume 10 Issue 2, February-2025
DOI (Digital Object Identifier):
Page No: a640-a643 Country: pune, maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2502066 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2502066 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||