The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Machine Learning and Secure Image Transmission for Disease Forecasting
|
|
Author(s): Angotu Saida (Department of Electronics and Communication Engineering, KG Reddy College of Engineering and Technology, India), Mallareddy Adudhodla (Department of IT, CVR College of Engineering, Telangana, India), Niladri Maiti (Central Asian University, Tashkent, Uzbekistan), Krishna Murthy Inumula (Symbiosis International University, Pune, India), G. Kalaiarasi (Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India)and Lakshmi Chandrakanth Kasireddy (ThoughtSpot Inc., USA)
Copyright: 2025
Pages: 24
Source title:
Advanced Secure Transmission of Telemedicine-Based Bio-Medical Images
Source Author(s)/Editor(s): Binay Kumar Pandey (Department of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, India), A. Shaji George (TSM, Almarai Company, Saudi Arabia), Sameer Tiwari (George Mason University, USA), Salah A. Albermany (Kufa University, Iraq)and Ho Sy Hung (Hong Duc University, Vietnam)
DOI: 10.4018/979-8-3693-9821-0.ch008
Purchase
|
Abstract
The transformative potential of machine learning (ML) in disease forecasting is emphasizes how crucial secure transmission techniques are to maintaining the integrity of patient data. With the growing reliance of healthcare on sophisticated data analytics, machine learning (ML) models have become indispensable instruments for forecasting disease outbreaks and enhancing patient results. ML algorithms are able to detect patterns and trends that help with early detection and intervention in a variety of health conditions by examining large datasets that include clinical data, medical images, and environmental factors. But considering the increasing frequency of cyberattacks and data breaches in the healthcare industry, it is critical that this sensitive data be transmitted securely.
Related Content
|
Parth Nagar, Srinath M. S..
© 2027.
48 pages.
|
|
Swapnali Pravin Gaikwad, Saurabh Vinayak Hembade.
© 2027.
36 pages.
|
|
Titiksha Tulsidas Bhagat, Shweta Bondre, Vipin Bondre, Uma Yadav, Priya Dasarwar.
© 2027.
26 pages.
|
|
Anshik Kumar Tiwari, Brindha Subburaj.
© 2027.
22 pages.
|
|
Grace Shalini T., Pratham Shrivastav, Parthiv Gopa.
© 2027.
36 pages.
|
|
S. Aarthi, Jaypalsinh A. Gohil.
© 2027.
30 pages.
|
|
Arul Selvam P., Tamije Selvy P..
© 2027.
30 pages.
|
|
|