Jain V. Deep Learning for Healthcare Decision Making 2022 torrent

Textbook in PDF format

Health care today is known to suffer from siloed and fragmented data, delayed clinical communications, and disparate workflow tools due to the lack of interoperability caused by vendor-locked health care systems, lack of trust among data holders, and security/privacy concerns regarding data sharing. The health information industry is ready for big leaps and bounds in terms of growth and advancement.
This book is an attempt to unveil the hidden potential of the enormous amount of health information and technology. Throughout this book, we attempt to combine numerous compelling views, guidelines, and frameworks to enable personalized health care service options through the successful application of Deep Learning (DL) frameworks. The progress of the health-care sector will be incremental as it learns from associations between data over time through the application of suitable Artificial Intelligence (AI), Deep Learning frameworks, and patterns. The major challenge health care is facing is the effective and accurate learning of unstructured clinical data through the application of precise algorithms. Incorrect input data leading to erroneous outputs with false positives is intolerable in healthcare as patients’ lives are at stake. This book is written with the intent to uncover the stakes and possibilities involved in realizing personalized health-care services through efficient and effective Deep Learning algorithms.
Chapter 1 covered the basics of Deep Learning that relates to predictive analysis, healthcare statistics, and the objective of relating deep learning in healthcare.
Chapter 2 gives a brief review of Deep Learning, its various architecture, and convolutional neural networks. The authors have also explained how these deep learning technologies can help the healthcare domain to advance.
Chapter 3 reviewed the papers that utilize Artificial Intelligence on healthcare applications to provide better and remote solutions.
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Chapter 10 aimed to provide a detailed description of the relationship between blockchain and Machine Learning techniques to empower an IoT-based healthcare system.
The specific focus of this book will be on the application of deep learning in any area of health care, including clinical trials, telemedicine, health records management, etc.
Preface
Amalgamation of Deep Learning in Healthcare Systems
Deep Neural Network Architecture and Applications in Healthcare
The State of the Art of using Artificial Intelligence for Disease Identification and Diagnosis in Healthcare
Segmentation of MRI Images of Gliomas using Convolutional Neural Networks
Automatic Liver Tumor Segmentation from Computed Tomography Images Based on 2D and 3D Deep Neural Networks
Advancements in Deep Learning Techniques for Analyzing Electronic Medical Records
Telemedicine-based Development of M-Health Informatics using AI
Health Informatics System using Machine Learning Techniques
Blockchain in Healthcare: A Systematic Review and Future Perspectives
Fusion of Machine Learning and Blockchain Techniques in IoT based Smart Healthcare Systems