Prediction of Neurological Disorders Using Visual Saliency: Current Trends and Future Directions

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Author(s): Sreelakshmi S. (Indian Institute of Information Technology and Management - Kerala (IIITM-K), Thiruvananthapuram, India)and Anoop V. S. (Rajagiri College of Social Sciences (Autonomous), Kochi, India)
Copyright: 2021
Pages: 11
Source title: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Source Author(s)/Editor(s): Manikant Roy (Lovely Professional University, India)and Lovi Raj Gupta (Lovely Professional University, India)
DOI: 10.4018/978-1-7998-7188-0.ch001

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

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Abstract

Neurological disorders are diseases of the central and peripheral nervous system and most commonly affect middle- or old-age people. Accurate classification and early-stage prediction of such disorders are very crucial for prompt diagnosis and treatment. This chapter discusses a new framework that uses image processing techniques for detecting neurological disorders so that clinicians prevent irreversible changes that may occur in the brain. The newly proposed framework ensures reliable and accurate machine learning techniques using visual saliency algorithms to process brain magnetic resonance imaging (MRI). The authors also provide ample hints and dimensions for the researchers interested in using visual saliency features for disease prediction and detection.

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Prediction of Neurological Disorders Using Visual Saliency: Current Trends and Future Directions

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