Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

<Previous Article In Volume
Next Article In Volume>

Al-Powered Telemedicine Enhancing Remote Patient Care with Machine Learning

Authors
D. Srivalli1, *, Sivanaga Malleswara Rao Singu2, Indigibilli Sahithi3, S. Venkateswarlu4, Gandhavalla Sambasiva Rao5, T. Benarji6
1Assistant Professor, Dept of CSE-DS, MLR Institute of Technology, Dundigal, Hyderabad, Telangana, India
2Sr. Project Manager, Vensai Technologies Inc, Cumming, GA, 30040, USA
3Assistant Professor, Department of CSE- IoT, Mallareddy Engineering College (Autonomous), Maisammaguda, Dhulapally, Medchal, Hyderabad, Telangana, India
4Principal, Narasaraopeta Engineering College, Narasaraopeta, Andhra Pradesh, India
5Professor and HOD, Dept of IT, Nawab Shah Alam Khan College of Engineering & Technology, Hyderabad, Telangana, India
6Professor, Dept of CSE. Indur Institute of Engineering and Technology, Siddipet, Telangana, India
*Corresponding author. Email: dhupatisrivalli@gmail.com
Corresponding Author
D. Srivalli
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_101How to use a DOI?
Keywords
AI-powered telemedicine; remote patient care; machine learning; real-time diagnostics; patient monitoring; healthcare data analysis; personalized treatment
Abstract

Telemedicine based on AI solutions is the new trend in the healthcare industry that offers using the possibilities of ML in remote patient treatment, using integrated artificial intelligence algorithms ensures accurate diagnosis, development of individual patient plans, and effective patient oversight while offering telemedicine as a service of remote care. The purpose of this paper is to discuss how AI currently interfaces with telemedicine by drawing on its use of real-time diagnostics, patient monitoring, and analysis of health information. The methodology includes assessing the latest trends in deploying AI algorithm to Tm and evaluating the impact of the employed algorithms on the population. The outcomes show optimization of the solution’s benefits, including enhanced quality of remote care, decreased inpatient treatments, and increased involvement. The last section of the study is dedicated to the threats and possible improvements in AI integration into telemedicine solutions; the importance of ethical guidelines and secure data protection.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_101How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - D. Srivalli
AU  - Sivanaga Malleswara Rao Singu
AU  - Indigibilli Sahithi
AU  - S. Venkateswarlu
AU  - Gandhavalla Sambasiva Rao
AU  - T. Benarji
PY  - 2025
DA  - 2025/05/23
TI  - Al-Powered Telemedicine Enhancing Remote Patient Care with Machine Learning
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1219
EP  - 1227
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_101
DO  - 10.2991/978-94-6463-718-2_101
ID  - Srivalli2025
ER  -