1. Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial
- Author
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Mark E. Bittman, Susan Sharp, Curtis P. Langlotz, Matthew P. Lungren, Shailee V. Lala, David Eng, Alexander J. Towbin, Nishith Khandwala, Michael L. Francavilla, Brian M. Everist, Kirsten Ecklund, David B. Larson, Sarah Milla, Safwan Halabi, Ross W. Filice, Jayne Seekins, Sanjay P. Prabhu, Rebecca Dennis, Jin Long, Naomi Strubel, Arash R. Zandieh, Christopher G. Anton, Nancy R. Fefferman, Summer L. Kaplan, Cicero T. Silva, and Brian J. Dillon
- Subjects
Adult ,Male ,Adolescent ,Diagnostic aid ,Sensitivity and Specificity ,law.invention ,Randomized controlled trial ,law ,Artificial Intelligence ,Age Determination by Skeleton ,Radiologists ,Medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Prospective Studies ,Child ,business.industry ,Infant ,Reproducibility of Results ,Bone age ,Radiography ,Child, Preschool ,Radiographic Image Interpretation, Computer-Assisted ,Female ,Artificial intelligence ,business ,Algorithm - Abstract
Background Previous studies suggest that use of artificial intelligence (AI) algorithms as diagnostic aids may improve the quality of skeletal age assessment, though these studies lack evidence from clinical practice. Purpose To compare the accuracy and interpretation time of skeletal age assessment on hand radiograph examinations with and without the use of an AI algorithm as a diagnostic aid. Materials and Methods In this prospective randomized controlled trial, the accuracy of skeletal age assessment on hand radiograph examinations was performed with (
- Published
- 2021