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Investigation of Radiologist Diagnostic Difficulty Prediction Without CT Images
Kazumasa Kishimoto1, Masahiro Yakami1, Tomohiro Kuroda1
1Kyoto University, Japan.
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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