Investigation of Radiologist Diagnostic Workload Prediction without CT Images Using Multimodal Deep Learning

For radiologists to collaborate, work must be distributed equally to prevent any sense of unfairness. This study proposes a model to predict the workload of radiologists based on order information and patient data without CT images. The multimodal multiclass classifier showed the highest performance when combining structured data and text data. This suggested that features contributing to workload prediction include not only in the text data but also in the structured data.