 |
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: March 2026
Volume 11 | Issue 3
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 : 11
Issue Published : 118
Article Submitted : 21686
Article Published : 8549
Total Authors : 22487
Total Reviewer : 811
Total Countries : 159
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AI-Driven Healthcare System for Doctor Recommendation and Video Consultation Based on Facial Expression and Speech Analysis |
| Authors Name: | D.Mahalakshmi , J.Queensia Mary , G.Sowmiya Bharathi , A.Santhi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_203659
|
| Published Paper Id: | IJRTI2505119 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Telehealth refers to the use of digital technologies to provide healthcare services remotely, enabling patients to consult with healthcare providers without needing to visit physical healthcare facilities. While telehealth offers the convenience of remote access, it faces significant challenges in delivering holistic care, as it often lacks the ability to gauge a patient's emotional well-being or mental state during consultations. Current telehealth systems also fail to offer personalized doctor recommendations tailored to the specific needs of each patient, relying instead on more generalized care approaches. This project introduces an AI-powered healthcare system designed to overcome these limitations by integrating advanced machine learning techniques. It utilizes Temporal Convolutional Neural Networks (TCNN) for facial expression recognition to assess emotional states and Convolutional Neural Networks (CNN) for speech recognition to capture vocal patterns. Furthermore, Natural Language Processing (NLP) is employed to understand the semantic content of patient speech, enabling a comprehensive analysis of both emotional and physical well-being. A key feature of the system is the use of content-based filtering to recommend healthcare professionals best suited to the patient's condition, ensuring a more tailored approach to treatment. The integration of secure video consultation services allows for real-time monitoring and assessment of the patient's facial expressions and speech patterns during the consultation. The system also includes a feedback mechanism to continuously improve doctor recommendations and overall patient care. By providing personalized recommendations and real-time emotional insights, this AI-driven solution addresses the shortcomings of traditional telehealth services. This innovative system marks a significant step forward in telehealth, combining machine learning with human-centered care to deliver a better remote healthcare experience. |
| Keywords: | Telehealth, remote healthcare, AI-driven system, facial expression recognition, speech recognition, emotional well-being,Temporal Convolutional Neural Networks (TCNN), Convolutional Neural Networks (CNN), Natural Language Processing (NLP), content-based filtering,personalized doctor recommendation, video consultation, real-time monitoring, semantic analysis, machine learning in healthcare,patient-centric care, emotion analysis, speech-to-text, healthcare AI integration. |
| Cite Article: | "AI-Driven Healthcare System for Doctor Recommendation and Video Consultation Based on Facial Expression and Speech Analysis", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.b138-b142, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505119.pdf |
| Downloads: | 000456 |
| 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: IJRTI2505119
Registration ID:203659
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: b138-b142 Country: Kallakuruchi, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505119 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505119 |
| 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 © 2026 - All Rights Reserved - IJRTI | |||