ISSN2456-3315
Impact Factor10.57
UGC CAREApproved
Low Cost₹599 / $45
CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning
Authors
Hari S , Ben Jacob Koshy , Dhiya V Georgekutty , Kuriakose Antony , Shandry K K
Keywords
Artificial intelligence (AI) in health care, Patient-provider communication, Healthcare chat bots, AI driven patient engagement.
Abstract
Artificial intelligence (AI)-powered health care chatbots are becoming essential instruments in revolutionizing the provision of healthcare services by providing patients and healthcare professionals with dependable and promising prompt support. Advanced natural language processing and machine learning techniques are used by these chatbots to optimize several healthcare functions, including communication between patients and providers, disease prediction, triage in emergency departments, and scheduling of appointments. These systems facilitate improved patient engagement, improved clinical workflows, and early detection of potential health concerns through seamless interactions. Although artificial intelligence technologies hold the power to transform entire industries, it is very challenging to integrate such systems into healthcare frameworks, especially given algorithmic bias, ethical concerns, and security issues related to data privacy. This paper attempts to explore both sides of healthcare chatbots that is, revolutionizing patient care and the current pressing need to ensure equitable and transparent artificial intelligence systems. This will critically evaluate the ethical implications of algorithmic decision-making, the risks involved in data misuse, and the challenges faced in sustaining user trust, providing a framework for equitable and efficient implementation
Full Paper, Downloads & Preview
How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJRTI — journal style
"A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 1, page no.a590-a594, January-2025, Available :https://ijrti.org/papers/IJRTI2501072.pdf
APA — 7th edition
S, H., Koshy, B. J., Georgekutty, D. V., Antony, K., & K, S. K. (2025). A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning. International Journal for Research Trends and Innovation, 10(1), a590-a594. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072
MLA — 9th edition
S, Hari, et al. "A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning." International Journal for Research Trends and Innovation, vol. 10, no. 1, 2025, pp. a590-a594, https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072.
Chicago — 17th, bibliography
S, Hari, et al. "A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning." International Journal for Research Trends and Innovation 10, no. 1 (2025): a590-a594. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072.
Harvard — author–date
S, H. et al. (2025) 'A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning', International Journal for Research Trends and Innovation, 10(1), pp. a590-a594. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072
IEEE — numbered reference
H. S, B. J. Koshy, D. V. Georgekutty, K. Antony and S. K. K, "A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning," IJRTI, vol. 10, no. 1, pp. a590-a594, Jan. 2025.
Vancouver — biomedical
S H, Koshy BJ, Georgekutty DV, Antony K, K SK. A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning. IJRTI. 2025 Jan;10(1):a590-a594.
AMA — 11th edition
S H, Koshy BJ, Georgekutty DV, Antony K, K SK. A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning. IJRTI. 2025;10(1):a590-a594. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2501072,
author = {Hari S and Ben Jacob Koshy and Dhiya V Georgekutty and Kuriakose Antony and Shandry K K},
title = {A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {1},
pages = {a590-a594},
year = {2025},
month = {January},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - S, Hari
AU - Koshy, Ben Jacob
AU - Georgekutty, Dhiya V
AU - Antony, Kuriakose
AU - K, Shandry K
TI - A Survey on Implementation of Medical Chatbots Using Artificial Intelligence and Machine Learning
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 1
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072
SP - a590-a594
ER -
Issue
Volume 10 Issue 1,
January-2025
Pages : a590-a594
Other Publication Details
Paper Reg. ID
IJRTI_200290
Published Paper ID
IJRTI2501072
Downloads
205,636
Research Area
Computer Science & TechnologyÂ
Country
Manarcadu, Kerala, India
Published
January 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2501072.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2501072
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
UGC CARE Approved Journal — Transparent Peer-reviewed journal aligned with UGC’s 2025 suggestive parameters, with CrossRef DOI registration and Scopus Standard metadata on every published paper.
Licence
© 2025 — Authors hold the copyright of this article.
This work is licensed under a
Creative Commons Attribution 4.0 International License
and The Open Definition.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0),
which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Disclaimer:
The content, data and findings in this article are based on the authors’ research and have been
peer-reviewed for academic purposes only. Readers are advised to verify all information before practical
or commercial use. The journal and its editorial board are not liable for any errors, losses or
consequences arising from its use.
Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
