1st Edition
The Impact of Artificial Intelligence in Radiology
Implementation of artificial intelligence (AI) in radiology is an important topic of discussion. Advances in AI—which encompass machine learning, artificial neural networks, and deep learning—are increasingly being applied to diagnostic imaging. While some posit radiologists are irreplaceable, certain AI proponents have proposed to "stop training radiologists now." By compiling perspectives from experts from various backgrounds, this book explores the current state of AI efforts in radiology along with the clinical, financial, technological, and societal perspectives on the role and expected impact of AI in radiology.
Technology in medicine - disruptive innovation
Chapter 1: Clinical view
Ranson Liao
Chapter 2: Technological view
Suely Fazio Ferraciolli; Edson Saito; Eduardo Farina; Léo Max Feuerschuette Neto; Osvaldo Landi Junior; Felipe Campos Kitamura
Chapter 3: Societal view
Ribhav Gupta; Heena Shah; Rajiv Dharnipragada; Ronit Gupta
Chapter 4: Financial view
Charlene Liew Jin Yee
Radiology's role in medicine
Chapter 5: Clinical view
Christian Bluthgen
Chapter 6: Technological view
Abhishta Bhandari
Chapter 7: Societal view
Krithika Rangarajan
Chapter 8: Financial view
Youngmin Chu
What is AI?
Chapter 9: Clinical view
Christian Federau
Chapter 10: Technological view
Bilwaj Gaonkar
Chapter 11: Societal view
Amy Patel
Chapter 12: Financial view
Christian Park
Current state of AI in radiology
Chapter 13: Clinical view
Alexander Jacobs
Chapter 14: Technological view
Mireia Crispin Ortuzar
Chapter 15: Societal view
Suely Fazio Ferraciolli
Chapter 16: Financial view
Florian Dubost
AI applications in development
Chapter 17: Clinical view
Leonid Chepelev
Chapter 18: Technological view
Tyler Gathman
Chapter 19: Societal view
Jayashree Kalpathy-Cramer
Chapter 20: Financial view
David Wu
Potential of AI
Chapter 21: Clinical view
Joseph Maldjian
Chapter 22: Technological view
William Hsu
Chapter 23: Societal view
Amy Patel
Chapter 24: Financial view
David Wu
Expectations - radiologists' jobs, job satisfaction, salary, role in society
Chapter 25: Clinical view
Amy Patel
Chapter 26: Technological view
Dr Kline
Chapter 27: Societal view
Benard Botwe
Chapter 28: Financial view
Mohammad Aghazadeh
Attitudes - implementation feasibility
Chapter 29: Clinical view
Christina Malamateniou
Chapter 30: Technological view
David Wu; Alexander Jacobs
Chapter 31: Societal view
Risto Filippi
Chapter 32: Financial view
David Wu
Technology determinism
Chapter 33: Clinical view
Suely Fazio Ferraciolli
Chapter 34: Technological view
Rajiv Dharnipragada
Chapter 35: Societal view
Rajiv Dharnipragada
Chapter 36: Financial view
David Wu; Megan Kollitz
Biography
Adam E. M. Eltorai, MD, PhD completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University, followed by Radiology residency at Brigham and Women's Hospital/Harvard Medical School. He is interested in the development and clinical implementation of AI applications. Dr. Eltorai has published over 130 scientific journal articles and over 25 books.
Ian Pan, MD is currently a diagnostic radiology resident and former chief resident in the Brigham and Women’s Hospital/Harvard Medical School Diagnostic Radiology Residency Program. He graduated from the Program in Liberal Medical Education at Brown University where he received concurrent bachelor’s and master’s degrees in applied mathematics-Biology and Biostatistics in 2016, as well as his MD from the Warren Alpert Medical School in 2020. His expertise lies at the intersection of artificial intelligence and medical imaging, having won multiple international competitions sponsored by organizations such as the Radiological Society of North America and published over 30 peer-reviewed manuscripts in this domain.
H. Henry Guo, MD, PhD is a clinical professor in the Department of Radiology at the Stanford University School of Medicine. He received his MD and PhD in the department of Pathology at the University of Washington, followed by Radiology residency and fellowships in Nuclear Medicine and Thoracic Imaging at Stanford. Since joining the Stanford faculty in 2012, Dr. Guo focuses on cancer and lung diseases in his clinical practice and research, co-authoring over 70 research articles, book chapters, and web-based educational resources, and is a recognized expert in interpretation of thoracic CTs and PET-CTs. Dr. Guo is translating the use of quantitative CT and AI-enabled tools to clinical practice and collaborates with other faculty members as a part of the Center for Artificial Intelligence in Medicine & Imaging (AIMI) at Stanford on applications of AI to topics including interstitial lung diseases, early cancer detection, and pulmonary hypertension.
