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CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation
Infarcted brain tissue resulting from acute stroke readily shows up as h...
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An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction: Application to the 2019 fastMRI Challenge
Adaptive intelligence aims at empowering machine learning techniques wit...
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3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images
Automatic segmentation of anatomical structures with convolutional neura...
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Spatial sensitivity analysis for urban land use prediction with physics-constrained conditional generative adversarial networks
Accurately forecasting urban development and its environmental and clima...
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Towards an automated method based on Iterated Local Search optimization for tuning the parameters of Support Vector Machines
We provide preliminary details and formulation of an optimization strate...
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Generating Time-Based Label Refinements to Discover More Precise Process Models
Process mining is a research field focused on the analysis of event data...
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Mining Process Model Descriptions of Daily Life through Event Abstraction
Process mining techniques focus on extracting insight in processes from ...
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An Ensemble Boosting Model for Predicting Transfer to the Pediatric Intensive Care Unit
Our work focuses on the problem of predicting the transfer of pediatric ...
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Can Pretrained Neural Networks Detect Anatomy?
Convolutional neural networks demonstrated outstanding empirical results...
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Recognizing Abnormal Heart Sounds Using Deep Learning
The work presented here applies deep learning to the task of automated c...
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Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature
The enhancement and detection of elongated structures in noisy image dat...
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Heuristic Approaches for Generating Local Process Models through Log Projections
Local Process Model (LPM) discovery is focused on the mining of a set of...
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On Generation of Time-based Label Refinements
Process mining is a research field focused on the analysis of event data...
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Deeply-Supervised CNN for Prostate Segmentation
Prostate segmentation from Magnetic Resonance (MR) images plays an impor...
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Multiscale Event Detection in Social Media
Event detection has been one of the most important research topics in so...
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Condensed Memory Networks for Clinical Diagnostic Inferencing
Diagnosis of a clinical condition is a challenging task, which often req...
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Neural Paraphrase Generation with Stacked Residual LSTM Networks
In this paper, we propose a novel neural approach for paraphrase generat...
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A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language
Semantic roles play an important role in extracting knowledge from text....
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Personalized Driver Stress Detection with Multi-task Neural Networks using Physiological Signals
Stress can be seen as a physiological response to everyday emotional, me...
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Designing virus-resistant, high-performance networks: a game-formation approach
Designing an optimal network topology while balancing multiple, possibly...
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DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference
We present a novel deep learning architecture to address the natural lan...
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Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks
The MIMIC-CXR dataset is (to date) the largest publicly released chest x...
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Maximum weight spectrum codes with reduced length
A q-ary linear code of dimension k is called a maximum weight spectrum (...
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Minimum Labelling bi-Connectivity
A labelled, undirected graph is a graph whose edges have assigned labels...
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Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable
In this paper we study the prediction of heart rate from acceleration us...
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Learning behavioral context recognition with multi-stream temporal convolutional networks
Smart devices of everyday use (such as smartphones and wearables) are in...
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Patient Subtyping with Disease Progression and Irregular Observation Trajectories
Patient subtyping based on temporal observations can lead to significant...
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Clinical Concept Extraction with Contextual Word Embedding
Automatic extraction of clinical concepts is an essential step for turni...
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Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss
We present a fully convolutional neural network for segmenting ischemic ...
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Evolutionary Construction of Convolutional Neural Networks
Neuro-Evolution is a field of study that has recently gained significant...
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Learning a sparse database for patch-based medical image segmentation
We introduce a functional for the learning of an optimal database for pa...
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Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI
The quantification of myocardial perfusion MRI has the potential to prov...
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Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging
Limitations on bandwidth and power consumption impose strict bounds on d...
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Perceptual Image Anomaly Detection
We present a novel method for image anomaly detection, where algorithms ...
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Continual Learning for Domain Adaptation in Chest X-ray Classification
Over the last years, Deep Learning has been successfully applied to a br...
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Service Selection using Predictive Models and Monte-Carlo Tree Search
This article proposes a method for automated service selection to improv...
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4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model
We propose a hybrid controllable image generation method to synthesize a...
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