Performance Modelling And Scalability Optimization Of Feature Selection And Machine Learning Methods For Arrhythmia Scope Prediction Strategies

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Computer-aided decision-making supports clinical decision-making (CAD). Arrhythmia classification is a related topic that uses machine learning algorithms to help categorize various forms of arrhythmia. By putting these machine learning approaches into practice, we can prevent or at least lessen problems like incorrect diagnosis, human error, and incompetent medical practitioners. Since these computer-assisted decision-making systems were created using machine learning approaches, long-term clinical monitoring using them is typically favoured.

Description

Computer-aided decision-making supports clinical decision-making (CAD). Arrhythmia classification is a related topic that uses machine learning algorithms to help categorize various forms of arrhythmia. By putting these machine learning approaches into practice, we can prevent or at least lessen problems like incorrect diagnosis, human error, and incompetent medical practitioners. Since these computer-assisted decision-making systems were created using machine learning approaches, long-term clinical monitoring using them is typically favoured.

Book Details

Available Format

Paperback Print

ISBN

9789365546293

Language

English

Page Count

152

Published Year

2024

Size

6×9 in

Author

Dr.JYOTHI SREEDHAR

Publisher

OrangeBooks Publication

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