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E-grāmata: Artificial Intelligence: Applications in Healthcare Delivery [Taylor & Francis e-book]

  • Formāts: 336 pages, 20 Illustrations, black and white
  • Izdošanas datums: 03-Dec-2020
  • Izdevniecība: CRC Press
  • ISBN-13: 9780429317415
  • Taylor & Francis e-book
  • Cena: 146,74 €*
  • * this price gives unlimited concurrent access for unlimited time
  • Standarta cena: 209,63 €
  • Ietaupiet 30%
  • Formāts: 336 pages, 20 Illustrations, black and white
  • Izdošanas datums: 03-Dec-2020
  • Izdevniecība: CRC Press
  • ISBN-13: 9780429317415
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.
Foreword vii
Editor ix
Technical Reviewers xi
Contributors xiii
1 Algorithmic Medicine
1(14)
Sandeep Reddy
2 Use of Artificial Intelligence in the Screening and Treatment of Chronic Diseases
15(40)
Chaitanya Mamillapalli
Daniel J. Fox
Ramanath Bhandari
Ricardo Correa
Vishnu Vardhan Garla
Rahul Kashyap
3 AI and Drug Discovery
55(12)
Arash Keshavarzi Arshadi
Milad Salem
4 Mammographic Screening and Breast Cancer Management - Part 1
67(30)
James Condon
Lyle Palmer
5 Mammographic Screening and Breast Cancer Management - Part 2
97(12)
Mark R. Traill
6 Deep Learning for Drawing Insights from Patient Data for Diagnosis and Treatment
109(28)
Dinesh Kumar
Dharmendra Sharma
7 A Simple and Replicable Framework for the Implementation of Clinical Data Science
137(26)
Juan Luis Cruz
Mariano Provencio
Ernestina Menasalvas
8 Clinical Artificial Intelligence - Technology Application or Change Management?
163(20)
Christopher Pearce
Adam Mcleod
Anna Fragkoudi
Natalie Rinehart
9 Impacting Perioperative Quality and Patient Safety Using Artificial Intelligence
183(12)
Piyush Mathur
Jacek B. Cywinski
Francis A. Papay
10 Application of an Intelligent Stochastic Optimization Nonlinear Model
195(12)
Gonzalo Hernandez
Fernando A. Crespo
11 Audit of Artificial Intelligence Algorithms and Its Impact in Relieving Shortage of Specialist Doctors
207(16)
Vidur Mahajan
Vasanth Venugopal
12 Knowledge Management in a Learning Health System
223(10)
Uli K. Chetti Pally
13 Transfer Learning to Enhance Amenorrhea Status Prediction in Cancer and Fertility Data with Missing Values
233(28)
Xuetong Wu
Hadi Akbarzadeh Khorshidi
Uwe Aickelin
Zobaida Edib
Michelle Peate
14 AMD Severity Prediction and Explailiability Using Image Registration and Deep Embedded Clustering
261(12)
Dwarikanath Mahapatra
15 Application of Artificial Intelligence in Thyroidology
273(12)
Johnson Thomas
16 Use of Artificial Intelligence in Sepsis Detection and Management
285(12)
Neha Deo
Rahul Kashyap
17 Transforming Clinical Trials with Artificial Intelligence
297(10)
Stefanie Lip
Shyam Visweswaran
Sandosh Padmanabhan
18 An Industry Review of Neuromorphic Chips
307(14)
Deepak Kumar Gopalakrishnan
Aditya Ravishankar
Hamid Abdi
19 Artificial Empathy - An Artificial Intelligence Challenge
321(6)
Dharmendra Sharma
Balaji Bikshandi
Index 327
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.