Artificial Intelligence
Applications in Healthcare Delivery
1st Edition
Published on 2. December 2020
352 pages
978-1-000-21686-8 (ISBN)
Description
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.
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.
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
20 Illustrations, black and white
File size
8,36 MB
ISBN-13
978-1-000-21686-8 (9781000216868)
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
Book
12/2021
1st Edition
CRC Press
€51.40
Shipment within 15-20 days
Book
12/2020
1st Edition
CRC Press
€195.00
Shipment within 15-20 days
Person
Sandeep Reddy is currently an Associate Professor at the Deakin School of Medicine, Deakin University, Geelong, Australia. He is an academic and certified health informatician with medical and health informatic qualifications. In addition to his medical training and experience with health informatic projects, he has undergone artificial intelligence (AI) training through various sources. He is currently engaged in the design and development of AI models to diagnose and treat medical conditions. He is also advising several organizations about use of AI technology to address healthcare issues. Further, Sandeep has authored several AI and digital health related publications including a book chapter about application of AI in Healthcare.
Content
Chapter 1 Algorithmic Medicine Chapter 2 Use of Artificial Intelligence in the Screening and Treatment of Chronic Diseases Chapter 3 AI 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 Learning 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 Non-Linear Model Chapter 11 Audit of Artificial Intelligence Algorithms and its 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
