Artificial intelligence : applications in healthcare delivery / edited by Sandeep Reddy.
The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to anincreasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and h...
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| Language: | English |
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Boca Raton, FL :
Productivity Press,
2021.
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| 245 | 0 | 0 | |a Artificial intelligence : |b applications in healthcare delivery / |c edited by Sandeep Reddy. |
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| 545 | 0 | |a 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. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 1 Algorithmic Medicine -- Sandeep Reddy -- 2 Use of Artificial Intelligence in the Screening and Treatment of Chronic Diseases -- Chaitanya Mamillapalli, Daniel J. Fox, Ramanath Bhandari, Ricardo Correa, Vishnu Vardhan Garla and Rahul Kashyap -- 3 Al and Drug Discovery -- Arash Keshavarzi Arshadi and Milad Salem -- 4 Mammographic screening and Breast Cancer Management-Part 1 -- James Condon and Lyle Palmer -- 5 Mammographic screening and Breast Cancer Management-Part 2 -- Mark R. Trail -- 6 Deep Learing for Drawing Insights from Patient Data for Diagnosis and Treatment -- Dinesh Kumar -- 7 A Simple and Replicable Framework for the Implementaion of Clinical Data Science -- Juan Luis Cruz, Mariano Provencio, Ernestina Menasalvas -- 8 Clinical Artificial Intelligence -- technology application or change management? -- Christopher Pearce, Adam McLeod, Anna Fragkoudi, Natalie Rinehart -- 9 Impacting Perioperative quality and patient safeety usinf Artificial Intelligence -- Piyush Mathur, Jacek B. Cywinski, Francis Papay -- 10 Application of an Ittelligent Stochastic Optimization NonLinear Model -- Gonzalo Hernandez and Fernando A. Crespo -- 11 Audit of Artificial Intelligence Algorithms and it's impact in Relieving Shortage of Specialist Doctors -- Vidur Mahajan and Vasanth Venugopal -- 12 Knowledge Management in a Learning Health System -- Uli K. Chettipally -- 13 Transfer learning to enhance amenorrhea status prediction in cancer and fertility data with missing values -- Xuetong Wu, Hadi Akbarzadeh Khorshidi, Uwe Aickelin, Zobaida Edib and Michelle Peate -- 14 AMD Severity Prediction and Explainability Using Image Registration and Deep Embedded Clustering -- Dwarikanath Mahapatra -- 15 Application of Artificial Intelligence in Thyroidology -- Johnson Thomas -- 16 Use of Artificial Intelligence in Sepsis Detection and Management -- Neha Deo and Rahul Kashyap -- 17 Transforming Clinical Trials with Artificial Intelligence -- Stefanie Lip, Shyam Visweswaran and Sandosh Padmanabhan -- 18 An Industry Review of Neuromorphic Chips -- Deepak Kumar Gopalakrishnan, Aditya Ravishankar and Hamid Abdi -- 19 Artificial Empathy -- An Artificial Intelligence Challenge -- Dharmendra Sharma and Balaji Bikshandi. | |
| 520 | |a The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to anincreasing 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. | ||
| 588 | 0 | |a Print version record. | |
| 650 | 0 | |a Artificial intelligence |x Medical applications. |0 http://id.loc.gov/authorities/subjects/sh88003000. | |
| 650 | 0 | |a Medical care. |0 http://id.loc.gov/authorities/subjects/sh85082871. | |
| 650 | 7 | |a Artificial intelligence |x Medical applications. |2 fast |0 (OCoLC)fst00817267. | |
| 650 | 7 | |a Medical care. |2 fast |0 (OCoLC)fst01013753. | |
| 700 | 1 | |a Reddy, Sandeep, |e editor. | |
| 776 | 0 | 8 | |i Print version: |t Artificial intelligence. |d New York : Productivity Press, 2020 |z 9780367321512 |w (OCoLC)1197759391. |
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