Machine Learning Perspective in Cancer Research

View Sample PDF

Author(s): Aman Sharma (IT Department, Jaypee University of Information Technology, Solan, India)and Rinkle Rani (Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, Patiala, India)
Copyright: 2021
Pages: 22
Source title: Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Source Author(s)/Editor(s): Geeta Rani (Manipal University Jaipur, India)and Pradeep Kumar Tiwari (Manipal University Jaipur, India)
DOI: 10.4018/978-1-7998-2742-9.ch008

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Diagnosis and Practice / Medical Information Science Reference

Purchase

View Machine Learning Perspective in Cancer Research on the publisher's website for pricing and purchasing information.

Abstract

Advancement in genome sequencing technology has empowered researchers to think beyond their imagination. Researchers are trying their hard to fight against various genetic diseases like cancer. Artificial intelligence has empowered research in the healthcare sector. Moreover, the availability of opensource healthcare datasets has motivated the researchers to develop applications which can help in early diagnosis and prognosis of diseases. Further, next-generation sequencing (NGS) has helped to look into detailed intricacies of biological systems. It has provided an efficient and cost-effective approach with higher accuracy. The advent of microRNAs also known as small noncoding genes has begun the paradigm shift in oncological research. We are now able to profile expression profiles of RNAs using RNA-seq data. microRNA profiling has helped in uncovering their relationship in various genetic and biological processes. Here in this chapter, the authors present a review of the machine learning perspective in cancer research.

The IRMA Community

Research IRM

Machine Learning Perspective in Cancer Research

Purchase

Abstract

Related Content

IRMA Sponsors