Search Results for author:
Found 7 papers, 0 papers with code
4D CNN for semantic segmentation of cardiac volumetric sequences
We propose a 4D convolutional neural network (CNN) for the segmentation of retrospective ECG-gated cardiac CT, a series of single-channel volumetric data over time.
DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning
We find that DeepAAA exceeds literature-reported performance of radiologists on incidental AAA detection.
Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning approaches burdens each development task as time and resource intensive.
An Overview and Case Study of the Clinical AI Model Development Life Cycle for Healthcare Systems
Healthcare is one of the most promising areas for machine learning models to make a positive impact.
Federated Learning for Breast Density Classification: A Real-World Implementation
Building robust deep learning-based models requires large quantities of diverse training data.
Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19
These results demonstrate our deep metric learning based image retrieval model is highly efficient in the CXR retrieval, diagnosis and prognosis, and thus has great clinical value for the treatment and management of COVID-19 patients.
Development and Validation of a Deep Learning Model for Prediction of Severe Outcomes in Suspected COVID-19 Infection
Predictive risk scores for COVID-19 severe outcomes ("CO-RISK" score) were derived from model output and evaluated on the testing dataset, as well as compared to human performance.
