Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems (eBook, PDF)

Redaktion: Jena, Om Prakash; Farhaoui, Yousef; Astya, Parma Nand; Rakesh, Nitin; Bhushan, Bharat

• Format: PDF

Produktbeschreibung

This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to insure high quality data processing, medical image and signal analysis, and improved healthcare application.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 395
• Erscheinungstermin: 18. Mai 2022
• Englisch
• ISBN-13: 9781000486797
• Artikelnr.: 63616526

Autorenporträt

Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, and Odisha. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Nitin Rakesh is the Head of Computer Science & Engineering Department for B.Tech/M.Tech (CSE/IT), B.Tech CSE-IBM Specializations, B.Tech CSE-I Nurture, BCA/MCA, BSc/MSc-CS at School of Engineering and Technology,at Sharda University, India. Dr. Parma Nand is a Dean, School of Engineering Technology, Sharda University Greater Noida. Dr. Yousef Farhaoui is a Professor at Moulay Ismail University, Faculty of Sciences and Techniques, Morocco.

Inhaltsangabe

1. Machine Learning in Healthcare: An Introduction 2. A Machine Learning Approach to Identify Personality Traits from Social Media 3. In
uence of Content Strategies on Community Engagement over the Healthcare-Related Social Media Pages in India 4. The Impact of Social Media in Fighting Emerging Diseases: A Model-Based Study 5. Prediction of Diabetes Mellitus Using Machine Learning 6. Spectrogram Image Textural Descriptors for Lung Sound Classi
cation 7. Medical Image Analysis Using Machine Learning Techniques: A Systematic Review 8. Impact of Ensemble-Based Models on Cancer Classi
cation, Its Development, and Challenges 9. Performance Comparison of Different Machine Learning Techniques towards Prevalence of Cardiovascular Diseases (CVDs) 10. Deep Neural Networks in Healthcare Systems 11. Deep Learning and Multimodal Arti
cial Neural Network Architectures for Disease Diagnosis and Clinical Applications 12. A Temporal JSON Model to Represent Big Data in IoT-Based e-Health Systems 13. Use of UAVs in the Prevention, Control and Management of Pandemics 14. Implicit Ontology Changes Driven by Evolution of e-Health IoT Sensor Data in the
OWL Semantic Framework 15. Classi
cation of Text Data in Healthcare Systems - A Comparative Study 16. Predicting Air Quality Index with Machine Learning Models