Applied Smart Health Care Informatics
A Computational Intelligence Perspective
1st Edition
Published on 24. March 2022
Book
Hardback
224 pages
978-1-119-74317-0 (ISBN)
Description
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
* Includes a companion website with video tutorials for each chapter in the text
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.
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
* Includes a companion website with video tutorials for each chapter in the text
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.
More details
Series
Language
English
Place of publication
Hoboken
United States
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Dimensions
Height: 250 mm
Width: 175 mm
Thickness: 17 mm
Weight
572 gr
ISBN-13
978-1-119-74317-0 (9781119743170)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Sourav De | Rik Das | Siddhartha Bhattacharyya
Applied Smart Health Care Informatics
A Computational Intelligence Perspective
E-Book
02/2022
1st Edition
Wiley-ISTE
€114.99
Available for download
Sourav De | Rik Das | Siddhartha Bhattacharyya
Applied Smart Health Care Informatics
A Computational Intelligence Perspective
E-Book
02/2022
1st Edition
Wiley-ISTE
€114.99
Available for download
Persons
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.
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.
Content
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), Tamil Nadu, India
Chapter 9
Abnormal Slice Classification from MRI Volumes using Bilateral Symmetry Property of Human Head Scans
Kalaichelvi N., The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
T. Kalaiselvi, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
K. Somasundaram, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
Chapter 10
Conclusion
Siddhartha Bhattacharyya, Rajnagar Mahavidyalaya, Birbhum, India
Index [to be compiled by the Editors at proofreading stage]
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), Tamil Nadu, India
Chapter 9
Abnormal Slice Classification from MRI Volumes using Bilateral Symmetry Property of Human Head Scans
Kalaichelvi N., The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
T. Kalaiselvi, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
K. Somasundaram, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, India
Chapter 10
Conclusion
Siddhartha Bhattacharyya, Rajnagar Mahavidyalaya, Birbhum, India
Index [to be compiled by the Editors at proofreading stage]