A Smart Solution for Cancer Patient Monitoring Based on Internet of Medical Things Using Machine Learning Approach

The Internet of Medical Things (IoMT) is a huge, exciting new phenomenon that is changing the world of technology and innovating various industries, including healthcare. It has specific applications and changes in the medical world based on what can be done for clinical workflow models. The first a...

Full description

Saved in:
Bibliographic Details
Published inEvidence-based complementary and alternative medicine Vol. 2022; pp. 1 - 6
Main Authors Sriram, Arram, Sekhar Reddy, G., Anand Babu, G. L., Bachanna, Prashant, Gurpreet, Singh Chhabra, Moyal, Vishal, Shubhangi, D. C., Sahu, Anil Kumar, Bhonsle, Devanand, Madana Mohana, R., Srihari, K., Chamato, Fekadu Ashine
Format Journal Article
LanguageEnglish
Published New York Hindawi 24.06.2022
Hindawi Limited
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The Internet of Medical Things (IoMT) is a huge, exciting new phenomenon that is changing the world of technology and innovating various industries, including healthcare. It has specific applications and changes in the medical world based on what can be done for clinical workflow models. The first and most fundamental thing that IoMT does in healthcare is to bring a flood of new data into medical processes. In this study, an efficient Internet of Medical Things based cancer detection model was proposed. In fact, for many, new fitness monitors and watches are one of the best examples on the Internet; these mobile, portable, wearable devices can record real-time heart rate, blood pressure, and eye movement of cancer patients. These details are sent to doctors or anywhere else. The proposed method leads to a kind of big data renaissance in the health service. The proposed model gets more accuracy while comparing with the existing models. This will help the doctors to analyze the patients’ health report and provides better treatment.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Correction/Retraction-3
Academic Editor: Arpita Roy
ISSN:1741-427X
1741-4288
DOI:10.1155/2022/2056807