Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems  book cover
1st Edition

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

  • Available for pre-order. Item will ship after December 15, 2021
ISBN 9781032036724
December 15, 2021 Forthcoming by CRC Press
400 Pages 133 B/W Illustrations

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Book Description

The paramountcy of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and led to the modern age of machine learning, deep learning and internet of medical things (IoMT) with their proliferation, mobility and agility. This book will expose different dimensions of applications for computational intelligence and will explain its use in solving various biomedical and healthcare problems in the real world. 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 the high quality data processing, medical image and signal analysis, and improved healthcare application. The book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with the innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significance progress in the field of machine learning and deep learning in healthcare applications. This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Table of Contents

1. Machine Learning in Healthcare: an Introduction
Shruti Dambhare, Sanjay Kumar
2. A Machine Learning Approach to Identify Personality Traits from Social Media
Ahona Ghosh, Ankita Biswas, Kanyaka Chakraborty, Ananya Ghosh, Namrata Das, Nikita Ghosh
3. Influence of Content Strategies on Community Engagement over the Healthcare related social media pages in India
Ajitabh Dash
4. The Impact of Social media in fighting emerging diseases : A model based study
Anal Chatterjee, Suchandra Ganguly
5. Prediction of Diabetes Mellitus Using Machine Learning
Salliah Shafi Bhat, Gufran Ahmad Ansari
6. Spectrogram Image Textural Descriptors for Lung Sound Classification
Bhakti Kaushal, Smitha Raveendran, Mukesh Patil, Gajanan Birajdar
7. Medical Image Analysis using Machine Learning Techniques: a Systematic Review
Mustafa A. Al-Asadi, Sakir Tasdemİr
8. Impact of Ensemble-based Models on Cancer Prognosis, Its Development and Challenges
Barnali Sahu, Sitarashmi Sahu, Om Prakash Jena 
9. Performance Comparison of Different Machine Learning Techniques Towards Prevalence of Cardiovascular Disease (CVDs)
Sachin Kamley
10. Deep Neural Networks in Healthcare Systems
Biswajit R Bhowmik, Shrinidhi Anil Varna, Adarsh Kumar, Rahul Kumar
11. Deep Learning and Multimodal Artificial Neural Network Architectures for Disease Diagnosis and Clinical Applications
Jeena Thomas, Ebin Deni Raj
12. A Temporal JSON Model to Represent Big Data in IoT-based e-Health Systems
Zouhaier Brahmia, Fabio Grandi, Safa Brahmia, Rafik Bouaziz
13. Use of UAVs in the prevention, control and management of pandemics
Giuliana Bilotta, Vincenzo Barrile, Ernesto Bernardo, Antonino Fotia
14. Implicit Ontology Changes Driven by Evolution of e-Health IoT Sensor Data in the τOWL Semantic Framework
Zouhaier Brahmia, Fabio Grandi, Abir Zekri, Rafik Bouaziz
15. Classification of Text Data in Healthcare Systems – A Comparative Study
Ömer Köksal
16. Predicting Air Quality Index with Machine Learning Models
Abirami G, Girija R, Anindya Das, Navneeth Sreenivasan

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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.