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11/21/2022
Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models
Multivariate signals are prevalent in various domains, such as healthcar...
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07/22/2022
TRUST-LAPSE: An Explainable Actionable Mistrust Scoring Framework for Model Monitoring
Continuous monitoring of trained ML models to determine when their predi...
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02/28/2022
Supervised Machine Learning Algorithm for Detecting Consistency between Reported Findings and the Conclusions of Mammography Reports
Objective. Mammography reports document the diagnosis of patients' condi...
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07/18/2021
An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging
Federated learning enables multiple institutions to collaboratively trai...
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05/17/2021
COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTs
Chest X-rays of coronavirus disease 2019 (COVID-19) patients are frequen...
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02/02/2021
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation
Suboptimal generalization of machine learning models on unseen data is a...
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10/15/2020
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset
The reliability of machine learning models can be compromised when train...
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07/13/2020
Probabilistic bounds on data sensitivity in deep rectifier networks
Neuron death is a complex phenomenon with implications for model trainab...
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08/24/2019
Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis
Different convolutional neural network (CNN) models have been tested for...
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04/29/2019
Self-Attention Capsule Networks for Image Classification
We propose a novel architecture for image classification, called Self-At...
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03/18/2019
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI
Detecting and segmenting brain metastases is a tedious and time-consumin...
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11/27/2018
CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss
Fully-convolutional neural networks have achieved superior performance i...
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06/15/2018
A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization
We propose a scalable computerized approach for large-scale inference of...
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01/09/2018
Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives
We propose a deep learning model - Probabilistic Prognostic Estimates of...
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11/19/2017
Intelligent Word Embeddings of Free-Text Radiology Reports
Radiology reports are a rich resource for advancing deep learning applic...
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09/10/2017
Institutionally Distributed Deep Learning Networks
Deep learning has become a promising approach for automated medical diag...
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09/07/2017
Inferring Generative Model Structure with Static Analysis
Obtaining enough labeled data to robustly train complex discriminative m...
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03/19/2017
A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes
We propose a fully-automated method for accurate and robust detection an...
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12/01/2016
Computerized Multiparametric MR image Analysis for Prostate Cancer Aggressiveness-Assessment
We propose an automated method for detecting aggressive prostate cancer(...
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07/17/2016
Piecewise convexity of artificial neural networks
Although artificial neural networks have shown great promise in applicat...
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06/12/2016