1.3k citations · 1.3k across the 5 of their papers we have counts for
9 papers
Simulating time to event prediction with spatiotemporal echocardiography deep learning
Rohan Shad, Nicolas Quach, Robyn Fong +8
Integrating methods for time-to-event prediction with diagnostic imaging modalities is of considerable interest, as accurate estimates of survival requires accounting for censoring…
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
Yasuhide Miura, Yuhao Zhang, Emily Bao Tsai +2
Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying po…
SCREENet: A Multi-view Deep Convolutional Neural Network for Classification of High-resolution Synthetic Mammographic Screening Scans
Saeed Seyyedi, Margaret J. Wong, Debra M. Ikeda +1
Purpose: To develop and evaluate the accuracy of a multi-view deep learning approach to the analysis of high-resolution synthetic mammograms from digital breast tomosynthesis scree…
Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant
Bora Uyumazturk, Amirhossein Kiani, Pranav Rajpurkar +17
While artificial intelligence (AI) algorithms continue to rival human performance on a variety of clinical tasks, the question of how best to incorporate these algorithms into clin…
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Yuhao Zhang, Derek Merck, Emily Bao Tsai +2
Neural abstractive summarization models are able to generate summaries which have high overlap with human references. However, existing models are not optimized for factual correct…
Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis
Okyaz Eminaga, Mahmoud Abbas, Christian Kunder +5
Different convolutional neural network (CNN) models have been tested for their application in histological image analyses. However, these models are prone to overfitting due to the…