The Impact of Artificial Intelligence 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

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.

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.