Deep Learning in Biomedical and Health Informatics
Current Applications and Possibilities
1st Edition
Published on 26. September 2021
224 pages
978-1-000-42908-4 (ISBN)
Description
This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This book also includes applications and case studies across all areas of AI in healthcare data. The editors also aim to provide new theories, techniques, developments, and applications of deep learning, and to solve emerging problems in healthcare and other domains. This book is intended for computer scientists, biomedical engineers, and healthcare professionals researching and developing deep learning techniques.
In short, the volume :
Discusses the relationship between AI and healthcare, and how AI is changing the health care industry.
Considers uses of deep learning in diagnosis and prediction of disease spread.
Presents a comprehensive review of research applying deep learning in health informatics across multiple fields.
Highlights challenges in applying deep learning in the field.
Promotes research in ddeep llearning application in understanding the biomedical process.
Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India.
Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA.
Dr.. Onur Dogan is an assistant professor at Izmir Bakircay University, Turkey.
Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal.
Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.
In short, the volume :
Discusses the relationship between AI and healthcare, and how AI is changing the health care industry.
Considers uses of deep learning in diagnosis and prediction of disease spread.
Presents a comprehensive review of research applying deep learning in health informatics across multiple fields.
Highlights challenges in applying deep learning in the field.
Promotes research in ddeep llearning application in understanding the biomedical process.
Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India.
Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA.
Dr.. Onur Dogan is an assistant professor at Izmir Bakircay University, Turkey.
Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal.
Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Illustrations
24 Tables, black and white; 26 Line drawings, black and white; 35 Halftones, black and white; 61 Illustrations, black and white
ISBN-13
978-1-000-42908-4 (9781000429084)
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
M. A. Jabbar | Ajith Abraham | Onur Dogan
Deep Learning in Biomedical and Health Informatics
Current Applications and Possibilities
Book
09/2023
1st Edition
CRC Press
€76.30
Shipment within 15-20 days
M. A. Jabbar | Ajith Abraham | Onur Dogan
Deep Learning in Biomedical and Health Informatics
Current Applications and Possibilities
Book
09/2021
1st Edition
CRC Press
€170.80
Shipment within 15-20 days
M. A. Jabbar | Ajith Abraham | Onur Dogan
Deep Learning in Biomedical and Health Informatics
Book
09/2021
CRC Press
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Persons
Dr. M. A. JABBAR is a Professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India.
Dr Ajith Abraham is the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing and a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013).
Dr. Onur Dogan is an assistant professor at Izmir Bakircay University.
Dr Ana Madureira has a PhD degree in Production and Systems from University of Minho, Portugal.
Dr. Sanju Tiwari is a Senior Researcher at Universidad Autonoma de Tamaulipas, Mexico.
Dr Ajith Abraham is the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing and a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013).
Dr. Onur Dogan is an assistant professor at Izmir Bakircay University.
Dr Ana Madureira has a PhD degree in Production and Systems from University of Minho, Portugal.
Dr. Sanju Tiwari is a Senior Researcher at Universidad Autonoma de Tamaulipas, Mexico.
Content
1. Foundations of Deep Learning and its Applications to Health Informatics.
2. Deep Knowledge Mining of Complete HIV Genome Sequences in Selected African Cohorts.
3. Review of Machine Learning Approach for Drug development Process.
4. A Detailed Comparison of Deep Neural Networks for Diagnosis of COVID-19.
5. Deep Learning in BioMedical Applications: Detection of Lung Disease with Convolutional Neural Networks
6. Deep Learning Methods For Diagnosis Of Covid-19 using Radiology Images And Genome Sequences: Challenges And Limitations.
7. Applications of Lifetime Modeling with Competing Risks in Biomedical Sciences.
8. PeNLP Parser: An Extraction and Visualization Tool for Precise Maternal, Neonatal and Child Healthcare Geo-locations from Unstructured Data.
9. Recent Trends in Deep learning, Challenges and Opportunities
2. Deep Knowledge Mining of Complete HIV Genome Sequences in Selected African Cohorts.
3. Review of Machine Learning Approach for Drug development Process.
4. A Detailed Comparison of Deep Neural Networks for Diagnosis of COVID-19.
5. Deep Learning in BioMedical Applications: Detection of Lung Disease with Convolutional Neural Networks
6. Deep Learning Methods For Diagnosis Of Covid-19 using Radiology Images And Genome Sequences: Challenges And Limitations.
7. Applications of Lifetime Modeling with Competing Risks in Biomedical Sciences.
8. PeNLP Parser: An Extraction and Visualization Tool for Precise Maternal, Neonatal and Child Healthcare Geo-locations from Unstructured Data.
9. Recent Trends in Deep learning, Challenges and Opportunities
