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A Survey of Generative Adversarial Networks for Synthesizing Structured Electronic Health Records

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Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group

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Electrocardiogram (ECG) Signal Processing

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Estimating long‐term treatment effects in observational data: A comparison of the performance of different methods under real‐world uncertainty

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Association Rule Mining: Models and Algorithms

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Reproducing Kernel Hilbert Spaces in Probability and Statistics

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RNN and LSTM

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Continuous Patient-Centric Sequence Generation via Sequentially Coupled Adversarial Learning

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Semi-supervised and Task-Driven Data Augmentation

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Data Augmentation with GAN: Improving Chest X-Ray Pathologies Prediction on Class-Imbalanced Cases

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Medical Time-Series Data Generation Using Generative Adversarial Networks

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SMOOTH-GAN: Towards Sharp and Smooth Synthetic EHR Data Generation

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Synthesizing Quality Open Data Assets from Private Health Research Studies

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PART-GAN: Privacy-Preserving Time-Series Sharing

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A Review of Attribute Disclosure Control

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The EU General Data Protection Regulation (GDPR)

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Noise Reduction in Speech Processing

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The Wasserstein distance and approximation theorems

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Acquisition of ICU data: concepts and demands

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A comprehensive review on GANs for time-series signals

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Sharpness-Aware Low-Dose CT Denoising Using Conditional Generative Adversarial Network

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Systematic Review of Generative Adversarial Networks (GANs) for Medical Image Classification and Segmentation

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Healthcare Cramér Generative Adversarial Network (HCGAN)

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Limitations of the Randomized Controlled Trial in Evaluating Population-Based Health Interventions

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Propensity score synthetic augmentation matching using generative adversarial networks (PSSAM-GAN)

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Applications of artificial intelligence in drug development using real-world data

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Security and privacy of electronic health records: Concerns and challenges

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Synthea™ Novel coronavirus (COVID-19) model and synthetic data set

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Unsupervised X-ray image segmentation with task driven generative adversarial networks

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Generation and evaluation of privacy preserving synthetic health data

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Synthetic data generation for tabular health records: A systematic review

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Effects of early intervention on cognitive function of low birth weight preterm infants

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Personalised medicine in the UK

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Information Systems Support for Emergency Medicine

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Detecting Drug Interactions From Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels

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Synthetic data in machine learning for medicine and healthcare

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Early prediction of circulatory failure in the intensive care unit using machine learning

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Deep learning-enabled medical computer vision

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An overview of clinical decision support systems: benefits, risks, and strategies for success

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Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications

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Adversarial interference and its mitigations in privacy-preserving collaborative machine learning

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MIMIC-III, a freely accessible critical care database

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The eICU Collaborative Research Database, a freely available multi-center database for critical care research

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Inpatient transfers to the intensive care unit

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Seminars in radiation oncology

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A Randomized Trial of Intensive versus Standard Blood-Pressure Control

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The use of simulated patients in medical education: AMEE Guide No 42

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Organisational factors underpinning intra-hospital transfers: a guide for evaluating context in quality improvement

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Health informatics and EHR to support clinical research in the COVID-19 pandemic: an overview

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MissForest—non-parametric missing value imputation for mixed-type data

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Heart failure in younger patients: the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC)

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Genomic data imputation with variational auto-encoders

inferredcites →https://doi.org/10.1093/ije/28.2.319openalex-snapshot

Simple sample size calculation for cluster-randomized trials

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Data Resource Profile: Clinical Practice Research Datalink (CPRD)

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Generating sequential electronic health records using dual adversarial autoencoder

inferredcites →https://doi.org/10.1093/jamia/ocaa262openalex-snapshot

SynTEG: a framework for temporal structured electronic health data simulation

inferredcites →https://doi.org/10.1093/jamia/ocw021openalex-snapshot

Missing clinical and behavioral health data in a large electronic health record (EHR) system

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Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review

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Synthesizing electronic health records using improved generative adversarial networks

inferredcites →https://doi.org/10.1093/jamia/ocz161openalex-snapshot

Ensuring electronic medical record simulation through better training, modeling, and evaluation

inferredcites →https://doi.org/10.1097/ccm.0000000000004916openalex-snapshot

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example*

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Jensen-Shannon divergence as a measure of distinguishability between mixed quantum states

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PhysioNet: a Web-based resource for the study of physiologic signals

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GAN-Based Semi-Supervised Learning Approach for Clinical Decision Support in Health-IoT Platform

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Continual learning of longitudinal health records

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Grouped Correlational Generative Adversarial Networks for Discrete Electronic Health Records

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StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation

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Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

inferredcites →https://doi.org/10.1109/icdm.2017.93openalex-snapshot

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records

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Categorical EHR Imputation with Generative Adversarial Nets

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Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems

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Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN)

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Generative Adversarial Networks: An Overview

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A Review on Machine Learning for EEG Signal Processing in Bioengineering

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Machine Learning for Clinical Outcome Prediction

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Membership Inference Attacks Against Machine Learning Models

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The singular value decomposition: Its computation and some applications

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Decoupled Learning for Conditional Adversarial Networks

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Barriers and opportunities for the clinical implementation of therapeutic drug monitoring in oncology

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SOME PRACTICAL GUIDANCE FOR THE IMPLEMENTATION OF PROPENSITY SCORE MATCHING

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Why we need observational studies to evaluate the effectiveness of health care

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Biases in electronic health record data due to processes within the healthcare system: retrospective observational study

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Confounding and confounders

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Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients

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Calculation of the Wasserstein Distance Between Probability Distributions on the Line

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Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

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Multi-layer Representation Learning for Medical Concepts

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Deep Learning with Differential Privacy

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Globally and locally consistent image completion

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Mining Electronic Health Records (EHRs)

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The limits of differential privacy (and its misuse in data release and machine learning)

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Concurrent imputation and prediction on EHR data using bi-directional GANs

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Transformers in Vision: A Survey

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Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements

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Generative Adversarial Networks in Time Series: A Systematic Literature Review

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Diffusion Models: A Comprehensive Survey of Methods and Applications

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Uses of Electronic Health Records for Public Health Surveillance to Advance Public Health

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Primary and Secondary Care Consultations in Elderly Demented Individuals in France

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Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing

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Long Short-Term Memory

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Correlational Neural Networks

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Transformers for Tabular Data Representation: A Survey of Models and Applications

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The class imbalance problem detecting adverse drug reactions in electronic health records

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Generation and evaluation of synthetic patient data

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Ethical issues in pragmatic randomized controlled trials: a review of the recent literature identifies gaps in ethical argumentation

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Treatment effect prediction with adversarial deep learning using electronic health records

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The dangers of parathyroid biopsy

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Bayesian Nonparametric Modeling for Causal Inference

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Ubiquitous Computing Fundamentals

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The Effects of the Irregular Sample and Missing Data in Time Series Analysis

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Covariance Adjustment in Randomized Experiments and Observational Studies

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Distributions of the Kullback–Leibler divergence with applications

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Patient, family and provider experiences with transfers from intensive care unit to hospital ward: a multicentre qualitative study

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The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus

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The Algorithmic Foundations of Differential Privacy

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Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs

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mice: Multivariate Imputation by Chained Equations inR

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Machine Learning for Clinical Decision-Making: Challenges and Opportunities

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Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?

inferredcites →https://doi.org/10.2196/35734openalex-snapshot

Utility Metrics for Evaluating Synthetic Health Data Generation Methods: Validation Study

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Introduction to Semi-Supervised Learning

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Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?

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Statistical Analysis with Missing Data.

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LOGAN: Membership Inference Attacks Against Generative Models

inferredcites →https://doi.org/10.24963/ijcai.2019/429openalex-snapshot

E²GAN: End-to-End Generative Adversarial Network for Multivariate Time Series Imputation

inferredcites →https://doi.org/10.29012/jpc.v1i1.568openalex-snapshot

Global Measures of Data Utility for Microdata Masked for Disclosure Limitation

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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

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The class imbalance problem: A systematic study1

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Cancer Statistics, 2002

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The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation

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Conditional Generative Adversarial Networks for Individualized Treatment Effect Estimation and Treatment Selection

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On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid

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Fast Kd-Trees for the Kullback-Leibler Divergence and Other Decomposable Bregman Divergences

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Diagnostic Analysis of Patients with Essential Hypertension Using Association Rule Mining

inferredcites →https://doi.org/10.48550/arxiv.1406.2661openalex-snapshot

Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1411.1784openalex-snapshot

Conditional Generative Adversarial Nets

inferredcites →https://doi.org/10.48550/arxiv.1511.01844openalex-snapshot

A note on the evaluation of generative models

inferredcites →https://doi.org/10.48550/arxiv.1511.06434openalex-snapshot

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1602.03686openalex-snapshot

Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction

inferredcites →https://doi.org/10.48550/arxiv.1606.01583openalex-snapshot

Semi-Supervised Learning with Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1610.05755openalex-snapshot

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

inferredcites →https://doi.org/10.48550/arxiv.1611.01144openalex-snapshot

Categorical Reparameterization with Gumbel-Softmax

inferredcites →https://doi.org/10.48550/arxiv.1611.01799openalex-snapshot

Generative Adversarial Networks as Variational Training of Energy Based Models

inferredcites →https://doi.org/10.48550/arxiv.1701.00160openalex-snapshot

NIPS 2016 Tutorial: Generative Adversarial Networks

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Towards Principled Methods for Training Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1702.08431openalex-snapshot

Boundary-Seeking Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1705.09783openalex-snapshot

Good Semi-supervised Learning that Requires a Bad GAN

inferredcites →https://doi.org/10.48550/arxiv.1705.10743openalex-snapshot

The Cramer Distance as a Solution to Biased Wasserstein Gradients

inferredcites →https://doi.org/10.48550/arxiv.1710.10196openalex-snapshot

Progressive Growing of GANs for Improved Quality, Stability, and Variation

inferredcites →https://doi.org/10.48550/arxiv.1712.00164openalex-snapshot

Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories

inferredcites →https://doi.org/10.48550/arxiv.1802.06739openalex-snapshot

Differentially Private Generative Adversarial Network

inferredcites →https://doi.org/10.48550/arxiv.1807.01202openalex-snapshot

Generating Multi-Categorical Samples with Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1812.00547openalex-snapshot

Semi-supervised Rare Disease Detection Using Generative Adversarial Network

inferredcites →https://doi.org/10.48550/arxiv.1812.05676openalex-snapshot

A Probe Towards Understanding GAN and VAE Models

inferredcites →https://doi.org/10.48550/arxiv.1901.09024openalex-snapshot

Diversity-Sensitive Conditional Generative Adversarial Networks

inferredcites →https://doi.org/10.48550/arxiv.1902.10666openalex-snapshot

Improving Missing Data Imputation with Deep Generative Models

inferredcites →https://doi.org/10.48550/arxiv.1906.01217openalex-snapshot

Convergence of Learning Dynamics in Stackelberg Games

inferredcites →https://doi.org/10.48550/arxiv.1907.01022openalex-snapshot

Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks

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Generative Adversarial Networks (GANs): An Overview of Theoretical Model, Evaluation Metrics, and Recent Developments

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Denoising Diffusion Probabilistic Models

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A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

inferredcites →https://doi.org/10.48550/arxiv.2012.04580openalex-snapshot

Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods

inferredcites →https://doi.org/10.48550/arxiv.2105.05233openalex-snapshot

Diffusion Models Beat GANs on Image Synthesis

inferredcites →https://doi.org/10.48550/arxiv.2109.02543openalex-snapshot

Generation of Synthetic Electronic Health Records Using a Federated GAN

inferredcites →https://doi.org/10.48550/arxiv.2302.14679openalex-snapshot

Synthesizing Mixed-type Electronic Health Records using Diffusion Models

inferredcites →https://doi.org/10.5121/ijdkp.2015.5201openalex-snapshot

A Review on Evaluation Metrics for Data Classification Evaluations

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Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature

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A kernel two-sample test

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The common problem of rare disease in general practice

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