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Investigation of Radiologist Diagnostic Difficulty Prediction Without CT Images
Kazumasa Kishimoto, Masahiro Yakami, Tomohiro Kuroda
1746 - 1747
10.3233/SHTI240765
Research Article
Studies in Health Technology and Informatics
Volume 316: Digital Health and Informatics Innovations for Sustainable Health Care Systems
Abstract

For better collaboration among radiologists, the interpretation workload should be evaluated, considering the difference in difficulty for interpreting each case. However, objective evaluation of difficulty is challenging. This study proposes a multimodal classifier of structural and textual data to predict difficulty based on order information and patient data without using images. The classifier showed performance with a specificity of 0.9 and an accuracy of 0.7.

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