
Artificial Intelligence in Radiology, An Issue of Radiologic Clinics of North America: Volume 59-6
Volume 59-6
Daniel L. Rubin(Editor)
Elsevier (Publisher)
Published on 2. November 2021
Book
Hardback
240 pages
978-0-323-81355-6 (ISBN)
Description
Approx. 240 pages
More details
Series
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 254 mm
Width: 178 mm
Weight
590 gr
ISBN-13
978-0-323-81355-6 (9780323813556)
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
Person
Editor
Professor of Biomedical Data Science, Radiology, and Medicine
Department of Biomedical Data Science
Stanford University
Medical School Office Building (MSOB)
Room X-335, MC 5464
1265 Welch Road
Stanford, CA 94305-5479
Department of Biomedical Data Science
Stanford University
Medical School Office Building (MSOB)
Room X-335, MC 5464
1265 Welch Road
Stanford, CA 94305-5479
Content
Basic Artificial Intelligence Techniques: Natural Language Processing of Radiology Reports
Basic Artificial Intelligence Techniques: Machine Learning and Deep Learning
Basic Artificial Intelligence Techniques: Evaluation of Artificial Intelligence Performance
Optimization of Radiology Workflow with Artificial Intelligence
Upstream Machine Learning in Radiology
Clinical Artificial Intelligence Applications in Radiology: Chest and Abdomen
Clinical Artificial Intelligence Applications in Radiology: Neuro
Clinical Artificial Intelligence Applications: Musculoskeletal
Clinical Artificial Intelligence Applications: Breast Imaging
Artificial Intelligence Enabling Radiology Reporting
Artificial Intelligence for Quality Improvement in Radiology
Separating Hope from Hype: Artificial Intelligence Pitfalls and Challenges in Radiology
Regulatory Issues and Challenges to Artificial Intelligence Adoption
Future Directions in Artificial Intelligence
Basic Artificial Intelligence Techniques: Machine Learning and Deep Learning
Basic Artificial Intelligence Techniques: Evaluation of Artificial Intelligence Performance
Optimization of Radiology Workflow with Artificial Intelligence
Upstream Machine Learning in Radiology
Clinical Artificial Intelligence Applications in Radiology: Chest and Abdomen
Clinical Artificial Intelligence Applications in Radiology: Neuro
Clinical Artificial Intelligence Applications: Musculoskeletal
Clinical Artificial Intelligence Applications: Breast Imaging
Artificial Intelligence Enabling Radiology Reporting
Artificial Intelligence for Quality Improvement in Radiology
Separating Hope from Hype: Artificial Intelligence Pitfalls and Challenges in Radiology
Regulatory Issues and Challenges to Artificial Intelligence Adoption
Future Directions in Artificial Intelligence