Artificial Intelligence : Applications in Healthcare Delivery

Title: Artificial Intelligence : Applications in Healthcare Delivery
Author: Sandeep Reddy
ISBN: 0367321513 / 9780367321512
Format: Hard Cover
Pages: 352
Publisher: Productivity Press
Year: 2020
Availability: 2 to 3 weeks

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The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery.

Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.

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Preface

Chapter 1 : Algorithmic Medicine
Chapter 2 : Use of Artificial Intelligence in the Screening and Treatment of Chronic Diseases
Chapter 3 : Al and Drug Discovery
Chapter 4 : Mammographic Screening and Breast Cancer Management-Part 1
Chapter 5 : Mammographic Screening and Breast Cancer Management-Part 2
Chapter 6 : Deep Learing for Drawing Insights from Patient Data for Diagnosis and Treatment
Chapter 7 : A Simple and Replicable Framework for The Implementation of Clinical Data Science
Chapter 8 : Clinical Artificial Intelligence - Technology Application or Change Management?
Chapter 9 : Impacting Perioperative Quality and Patient Safety using Artificial Intelligence
Chapter 10 : Application of an Intelligent Stochastic Optimization Nonlinear Model
Chapter 11 : Audit of Artificial Intelligence Algorithms and It's Impact in Relieving Shortage of Specialist Doctors
Chapter 12 : Knowledge Management in a Learning Health System
Chapter 13 : Transfer Learning to Enhance Amenorrhea Status Prediction in Cancer and Fertility Data with Missing Values
Chapter 14 : AMD Severity Prediction and Explainability using Image Registration and Deep Embedded Clustering
Chapter 15 : Application of Artificial Intelligence in Thyroidology
Chapter 16 : Use of Artificial Intelligence in Sepsis Detection and Management
Chapter 17 : Transforming Clinical Trials with Artificial Intelligence
Chapter 18 : An Industry Review of Neuromorphic Chips
Chapter 19 : Artificial Empathy - An Artificial Intelligence Challenge

Index