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Found 5 papers, 1 papers with code
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction
The first is deterioration prediction from a single image, where our model achieves an area under receiver operating characteristic curve (AUC) of 0. 742 for predicting an adverse event within 96 hours (compared to 0. 703 with supervised pretraining) and an AUC of 0. 765 for predicting oxygen requirements greater than 6 L a day at 24 hours (compared to 0. 749 with supervised pretraining).
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held on December 8, 2018 in Montreal, Canada.
Explainability Matters: Backdoor Attacks on Medical Imaging
Extensive evaluation of a state-of-the-art architecture demonstrates that by introducing images with few-pixel perturbations into the training set, an attacker can execute the backdoor successfully without having to be involved with the training procedure.
An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates
Teaching artificial intelligence (AI) is challenging.
Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data
Breast cancer screening, primarily conducted through mammography, is often supplemented with ultrasound for women with dense breast tissue.
