IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Applications of Machine Learning in Disease Pre-screening

Applications of Machine Learning in Disease Pre-screening
View Sample PDF
Author(s): Upendra Kumar (Institute of Engineering and Technology Lucknow, India)
Copyright: 2021
Pages: 33
Source title: Research Anthology on Artificial Intelligence Applications in Security
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-7705-9.ch049

Purchase

View Applications of Machine Learning in Disease Pre-screening on the publisher's website for pricing and purchasing information.

Abstract

Computers in disease prescreening are utilized to interpret medical information. This is known as computer-aided pre-screening tool (CAPST). CAPST helps in improving the accuracy of diagnosis in medicine. The medical experts usually take the outcome of the CAPST as a second opinion to make the final diagnostic decisions. Fast and accurate prediction of disease risk and diagnosis is crucial step for the successful treatment of an individual. The AI-based machine learning technology has undergone significant developments over the past few years and is successfully used in many intelligent applications covering problems of variety of domains. One of the most stimulating questions is whether these techniques can be successfully applied to medicine in disease pre-screening and diagnosis and what kind of data it requires to be trained and learned. There are so many real-time examples of the problems where machine learning methods are applied successfully, especially in medicine. Many of them showed significant improvement in classification accuracy.

Related Content

Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava. © 2024. 20 pages.
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima. © 2024. 52 pages.
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira. © 2024. 24 pages.
Fatih Pinarbasi. © 2024. 20 pages.
Stavros Kaperonis. © 2024. 25 pages.
Thomas Rui Mendes, Ana Cristina Antunes. © 2024. 24 pages.
Nuno Geada. © 2024. 12 pages.
Body Bottom