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06/14/2023
Towards trustworthy seizure onset detection using workflow notes
A major barrier to deploying healthcare AI models is their trustworthine...
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01/30/2023
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays
Image augmentations are quintessential for effective visual representati...
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08/24/2022
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Self supervised contrastive learning based pretraining allows developmen...
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06/17/2022
The Importance of Background Information for Out of Distribution Generalization
Domain generalization in medical image classification is an important pr...
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05/09/2022
Masked Co-attentional Transformer reconstructs 100x ultra-fast/low-dose whole-body PET from longitudinal images and anatomically guided MRI
Despite its tremendous value for the diagnosis, treatment monitoring and...
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04/14/2022
Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission
Measures to predict 30-day readmission are considered an important quali...
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11/23/2021
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR
Despite the routine use of electronic health record (EHR) data by radiol...
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11/18/2021
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Artificial intelligence (AI) provides a promising substitution for strea...
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06/24/2021
Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging
Collaborative learning, which enables collaborative and decentralized tr...
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02/23/2020
Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization
We introduce a novel ensembling method, Random Bundle (RB), that improve...
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01/26/2020
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives
Deep learning has proven to be an essential tool for medical image analy...
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12/27/2019
Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study
The purpose was to assess the clinical value of a novel DropOut model fo...
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12/18/2019
MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation
Magnetic resonance (MR) imaging is an essential diagnostic tool in clini...
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11/26/2019
Bounding Zolotarev numbers using Faber rational functions
By closely following a construction by Ganelius, we construct Faber rati...
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10/21/2019
Biologic and Prognostic Feature scores from Whole-Slide Histology Images Using Deep Learning
Histopathology is a reflection of the molecular changes and provides pro...
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10/11/2019
Deep Learning for Prostate Pathology
The current study detects different morphologies related to prostate pat...
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08/19/2019
Deep Active Lesion Segmentation
Lesion segmentation is an important problem in computer-assisted diagnos...
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03/26/2019
Cross-Modal Data Programming Enables Rapid Medical Machine Learning
Labeling training datasets has become a key barrier to building medical ...
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02/27/2019
A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers
We propose a hybrid sequential deep learning model to predict the risk o...
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02/13/2018
TVAE: Triplet-Based Variational Autoencoder using Metric Learning
Deep metric learning has been demonstrated to be highly effective in lea...
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05/17/2017
Optimizing and Visualizing Deep Learning for Benign/Malignant Classification in Breast Tumors
Breast cancer has the highest incidence and second highest mortality rat...
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10/02/2012
Classification of Hepatic Lesions using the Matching Metric
In this paper we present a methodology of classifying hepatic (liver) le...
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06/29/2012
