Paper Title

TELEHEALTH- ONLINE HEALTHCARE

Authors

Shubham Kaloge , Rohit Moriya , Rahul Bhujbal , Prajwal Patil

Keywords

Doctor consultation, Video Conference, Patient, Machine Learning, Encryption, Portal.

Abstract

As technology is growing rapidly, most of the manual systems are being replaced and becoming automated. In this context, we are going to create an easy, faster and smooth appointment system between doctor and patient. With the development of online healthcare consultations, more and more doctors provide medical consultation services online. However, due to the poor healthcare knowledge and high consultation fees, selecting a proper doctor becomes a difficult problem for many users. We are creating a system which uses recommendation model takes the real consultation data from online as the research object, fully testifying its effectiveness. Specifically, this model would make recommendation to patients on department and doctors based on patients’ information of symptoms, diagnosis and geographical location, as well as doctor’s specialty and their department. Our system uses online video call consultation and smart recommendation system for patient with different diseases. System also recommends pathology labs for user to do different testing. online doctor recommendation model integrates ontology characteristics and disease text mining. The model gives a relatively more accurate recommendation advice. Furthermore, the model also gives full consideration on patients” location factors. As a result, the proposed online doctor recommendation model would improve patients’ online consultation experience and offline treatment convenience, enriching the value of online pre-diagnosis data. We are creating a system which uses recommendation model takes the real consultation data from online as the research object, fully testifying its effectiveness. Specifically, this model would make recommendation to patients on department and doctors based on patients’ information of symptoms, diagnosis and geographical location, as well as doctor’s specialty and their department. Our system uses online video call consultation and smart recommendation system for patient with different diseases.Telehealth: Online healthcare recommends pathology labs for user to do different testing. online doctor recommendation model integrates ontology characteristics and disease text mining. The model gives a relatively more accurate recommendation advice. Furthermore, the model also gives full consideration on patients” location factors. As a result, the proposed online doctor recommendation model would improve patients’ online consultation experience and offline treatment convenience, enriching the value of online pre-diagnosis data

How To Cite

"TELEHEALTH- ONLINE HEALTHCARE", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.593 - 596, March-2023, Available :https://ijsdr.org/papers/IJSDR2303095.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : 593 - 596

Other Publication Details

Paper Reg. ID: IJSDR_204603

Published Paper Id: IJSDR2303095

Downloads: 000347154

Research Area: Engineering

Country: -, -, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303095

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303095

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

Article Preview

academia
publon
sematicscholar
googlescholar
scholar9
maceadmic
Microsoft_Academic_Search_Logo
elsevier
researchgate
ssrn
mendeley
Zenodo
orcid
sitecreex