Applied Smart Health Care Informatics

Applied Smart Health Care Informatics

Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare

Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies.

Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services.

• Provides an overview of different deep learning applications for intelligent healthcare informatics management

• Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management

• Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management

• Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques

• Examines the use of exploratory data analysis in intelligent healthcare informatics systems

Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.

Auteur

Dr. Sourav De, Associate Professor, Department of Computer Science and Engineering, Cooch Behar Government Engineering College, India.

Dr. Rik Das, Assistant Professor, Department of Information Technology, Xavier Institute of Social Service, India.

Dr. Siddhartha Bhattacharyya, Principal, Rajnagar Mahavidyalaya, India.

Dr. Ujjwal Maulik, Professor, Department of Computer Science and Engineering, Jadavpur University, India.

Résumé
Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services.

• Provides an overview of different deep learning applications for intelligent healthcare informatics management
• Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management
• Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management
• Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques
• Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.

Contenu
Table of Contents

Preface

About the Editors

List of Contributors [vendor to compile from COP info and contrib. spreadsheet]

Chapter 1
An Overview of Applied Smart Health Care Informatics in context of Computational Intelligence

Sourav De, Cooch Behar Government Engineering College, Cooch Behar, India

Rik Das, Xavier Institute of Social Service, Ranchi, India

Chapter 2
Artificial Intelligence for Lung Cancer Classification using PET-CT Scan
Kaushik Pratim Das, CHRIST (Deemed to be University) , Bangalore, India

Chandra J., CHRIST (Deemed to be University) , Bangalore, India

Nachamai M., Siemens Healthcare Pvt.Ltd ,

Chapter 3
Formal Methods for Security of Medical Devices
Srinivas Pinisetty, Indian Institute of Technology Bhubaneswar, India

Nathan Allen, University of Auckland, New Zealand

Hammond Pearce, NYU Tandon School of Engineering, USA

Mark Trew, University of Auckland, New Zealand

Manoj Singh Gaur, Indian Institute of Technology Jammu, India

Partha S Roop, University of Auckland, New Zealand

Chapter 4
Integration of two deep learning models for identifying gene signature in head and neck cancer from multi-omics data analysis
Suparna Saha, SyMeC Data Center, Indian Statistical Institute, Kolkata, India

Sumanta Ray, Aliah University, Kolkata, India

Sanghamitra Bandyopadhyay, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

Chapter 5
A Study of Computational Learning and IoT Applications to High-Throughput Array-based Sequencing and Medical Imaging data in Drug Discovery and Other Health Care Systems
Soham Choudhuri, Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, India

Saurav Mallik, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, USA

Bhaswar Ghosh, Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad, India

Tapas Si, Bankura Unnayani Institute of Engineering, Bankura, India

Tapas Bhadra, Aliah University, Kolkata, India

Ujjwal Maulik, Jadavpur University, Kolkata, India

Aimin Li, School of Computer Science and Engineering, Xi`an University of Technology, China

Chapter 6
Analysis of Breast Cancer Risk Factors Data: Association Rule Mining based on Ethnic Groups and Classification using Super Learning
Md Faisal Kabir, North Dakota State University, ND, USA

Simone A. Ludwig, North Dakota State University, ND, USA

Chapter 7
Neuro-Rough Hybridization for Recognition of Virus Particles from TEM Images
Debamita Kumar, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

Pradipta Maji, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

Chapter 8
Neural Network Optimizers for Brain Tumor Image Detection
T. Kalaiselvi, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India

*S. T. Padmapriya, The Gandhigram Rural Institute (Deemed to be University…