Sensitivity and Specificity Evaluation of Deep Learning Models for Detection of Pneumoperitoneum on Chest Radiographs

no code implementations • 17 Oct 2020 • Manu Goyal, Judith Austin-Strohbehn, Sean J. Sun, Karen Rodriguez, Jessica M. Sin, Yvonne Y. Cheung, Saeed Hassanpour

State-of-the-art deep learning models (ResNet101, InceptionV3, DenseNet161, and ResNeXt101) were trained on a subset of this dataset, and the automated classification performance was evaluated on the rest of the dataset by measuring the AUC, sensitivity, and specificity for each model.

Specificity

Self-Supervised Contextual Language Representation of Radiology Reports to Improve the Identification of Communication Urgency

no code implementations • 5 Dec 2019 • Xing Meng, Craig H. Ganoe, Ryan T. Sieberg, Yvonne Y. Cheung, Saeed Hassanpour

We pre-trained the BERT model on a large unlabeled corpus of radiology reports and used the resulting contextual representations in a final text classifier for communication urgency.

Self-Supervised Learning