Publications citing MIMIC-III Waveform Database v1.0

Utilizing Multimodal Feature Consistency to Detect Adversarial Examples on Clinical Summaries
Wenjie Wang, Youngja H. Park, Taesung Lee et al. Clinical Natural Language Processing Workshop (ClinicalNLP), 2020. Cites: paper

What went wrong and when? Instance-wise feature importance for time-series black-box models
Sana Tonekaboni, Shalmali D. Joshi, Kieran R. Campbell et al. neural information processing systems, 2020. Cites: paper

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study
Mark Sendak, William Ratliff, Dina Sarro et al. JMIR Medical Informatics, 2019. Cites: paper

Sensitivity of comorbidity network analysis
Jason Cory Brunson, Thomas P. Agresta, Reinhard Laubenbacher. JAMIA Open, 2019. Cites: paper

Accurate and reproducible prediction of ICU readmissions
Dinh-Phong Nguyen. medRxiv, 2019. Cites: paper

An Ensemble Machine Learning Model for the Early Detection of Sepsis from Clinical Data
Mengsha Fu, Jiabin Yuan, Menglin Lu et al. Computing in cardiology, 2019. Cites: paper

Natural language processing of MIMIC-III clinical notes for identifying diagnosis and procedures with neural networks
Siddhartha Nuthakki, Sunil Neela, Judy Wawira Gichoya et al. arXiv (Cornell University), 2019. Cites: paper

Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review
Shenda Hong, Yuxi Zhou, Junyuan Shang et al. arXiv (Cornell University), 2019. Cites: paper

Analyzing Medical Research Results Based on Synthetic Data and Their Relation to Real Data Results: Systematic Comparison From Five Observational Studies
Anat Reiner Benaim, Ronit Almog, Yuri Gorelik et al. JMIR Medical Informatics, 2019. Cites: paper

Central venous pressure and the risk of diuretic-associated acute kidney injury in patients after cardiac surgery
Ian Ellis McCoy, Maria E. Montez‐Rath, Glenn Matthew Chertow et al. American Heart Journal, 2019. Cites: paper

Improving Patient Cohort Identification using Neural Word Embedding with Structured Analysis
Md. Jahidul Islam, Julia Rahman, Md Khaled Ben Islam. International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), 2019. Cites: paper

Long Short-Term Memory Recurrent Neural Networks for Multiple Diseases Risk Prediction by Leveraging Longitudinal Medical Records
Tingyan Wang, Tian Yuan-xin, Robin G. Qiu. IEEE Journal of Biomedical and Health Informatics, 2019. Cites: paper

A Communication Efficient Collaborative Learning Framework for Distributed Features
Yang Liu, Yan Kang, Xinwei Zhang et al. arXiv (Cornell University), 2019. Cites: paper

Detection of Outlier Events in Continuous-Time Event Sequences
Siqi Liu, Miloš Hauskrecht. arXiv (Cornell University), 2019. Cites: paper

Event Outlier Detection in Continuous Time
Siqi Liu, Miloš Hauskrecht. PubMed, 2019. Cites: paper

Forecasting intracranial hypertension using multi-scale waveform metrics
Matthias Hüser, Adrian Kündig, Walter Karlen et al. Physiological Measurement, 2019. Cites: paper

Generative Neural Networks to infer Causal Mechanisms : algorithms and applications
Diviyan Kalainathan. 2019. Cites: paper

A comprehensive evaluation for the prediction of mortality in intensive care units with LSTM networks: patients with cardiovascular disease
Saumil Maheshwari, Aman Agarwal, Anupam Shukla et al. Biomedizinische Technik/Biomedical Engineering, 2019. Cites: paper

Tackling Overfitting in Boosting for Noisy Healthcare Data
Yubin Park, Joyce C. Ho. IEEE Transactions on Knowledge and Data Engineering, 2019. Cites: paper

Terminologies augmented recurrent neural network model for clinical named entity recognition
Ivan Lerner, Nicolás Paris, Xavier Tannier. Journal of Biomedical Informatics, 2019. Cites: paper

Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study
Benjamin Scott Glicksberg, Shohei Burns, Rob Currie et al. Journal of Medical Internet Research, 2019. Cites: paper

Sepsis World Model: A MIMIC-based OpenAI Gym "World Model" Simulator for Sepsis Treatment
Amirhossein Kiani, Chris Wang, Angela Xu. arXiv (Cornell University), 2019. Cites: paper

Transfer Learning for Clinical Time Series Analysis Using Deep Neural Networks
Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya et al. Journal of Healthcare Informatics Research, 2019. Cites: paper

MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports
Alistair E. W. Johnson, Tom Pollard, Seth J. Berkowitz et al. Scientific Data, 2019. Cites: paper

Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes
Jackson Steinkamp, Wasif Bala, Abhinav Sharma et al. Journal of Biomedical Informatics, 2019. Cites: paper

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity
Alberto Blanco, Olatz Perez-de-Viñaspre, Alicia Pérez et al. Computer Methods and Programs in Biomedicine, 2019. Cites: paper

Fluctuations of consciousness after stroke: Associations with the confusion assessment method for the intensive care unit (CAM-ICU) and potential undetected delirium
Michael E. Reznik, Lori A. Daiello, Bradford Thompson et al. Journal of Critical Care, 2019. Cites: paper

Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings
Shaika Chowdhury, Chenwei Zhang, Philip S. Yu et al. arXiv (Cornell University), 2019. Cites: paper

On classifying sepsis heterogeneity in the ICU: insight using machine learning
Zina M. Ibrahim, Honghan Wu, Ahmed Hamoud et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

Deep Physiological State Space Model for Clinical Forecasting
Yuan Xue, Denny Zhou, Nan Du et al. arXiv (Cornell University), 2019. Cites: paper

Identifying patients with pain in emergency departments using conventional machine learning and deep learning
Thanh Vu, Anthony N Nguyen, Nathan J. Brown et al. QUT ePrints (Queensland University of Technology), 2019. Cites: paper

Predicting ICD-9 code groups with fuzzy similarity based supervised multi-label classification of unstructured clinical nursing notes
Tushaar Gangavarapu, Aditya Jayasimha, Gokul S Krishnan et al. Knowledge-Based Systems, 2019. Cites: paper

A Hybrid Machine Learning Approach for Improving Mortality Risk Prediction on Imbalanced Data
Araek Tashkandi, Lena Wiese. International Conference on Information Integration and Web-based Applications & Services (iiWAS), 2019. Cites: paper

An adaptive term proximity based rocchio’s model for clinical decision support retrieval
Min Pan, Yue Zhang, Qiang Zhu et al. BMC Medical Informatics and Decision Making, 2019. Cites: paper

A study of deep learning methods for de-identification of clinical notes in cross-institute settings
Xi Yang, Tianchen Lyu, Qian Li et al. BMC Medical Informatics and Decision Making, 2019. Cites: paper

Big Data Analytics in Healthcare: Data-Driven Methods for Typical Treatment Pattern Mining
Chonghui Guo, Jingfeng Chen. Journal of Systems Science and Systems Engineering, 2019. Cites: paper

CTC-Attention based Non-Parametric Inference Modeling for Clinical State Progression
Riazat Ryan, Handong Zhao, Ming Shao. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

Developing a Registry of Healthcare-Associated Infections at Intensive Care Units in West China: Study Rationale and Patient Characteristics
Wen Wang, Shichao Zhu, Qiao He et al. Clinical Epidemiology, 2019. Cites: paper

DKDR: An Approach of Knowledge Graph and Deep Reinforcement Learning for Disease Diagnosis
Yuanyuan Jia, Zhiren Tan, Junxing Zhang. IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), 2019. Cites: paper

Incorporating medical code descriptions for diagnosis prediction in healthcare
Fenglong Ma, Yaqing Wang, Houping Xiao et al. BMC Medical Informatics and Decision Making, 2019. Cites: paper

Learning Temporal Relevance in Longitudinal Medical Notes
Cansu Şen, Thomas Hartvigsen, Xiangnan Kong et al. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension
Ye Xue, Diego Klabjan, Yuan Luo. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention
Cansu Şen, Thomas Hartvigsen, Xiangnan Kong et al. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

PPGAN: Privacy-Preserving Generative Adversarial Network
Yi Liu, Jialiang Peng, James J. Q. Yu et al. IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2019. Cites: paper

Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality
Pulkit Sharma, Farah E. Shamout, David Andrew Clifton. arXiv (Cornell University), 2019. Cites: paper

Privacy-preserving Heterogeneous Federated Transfer Learning
Dashan Gao, Yang Liu, Anbu Huang et al. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

Respiratory parameters and acute kidney injury in acute respiratory distress syndrome: a causal inference study
Tacyano Tavares Leite, Cícero Abdon Malheiro Gomes, Juan Miguel Cosquillo Valdivia et al. Annals of Translational Medicine, 2019. Cites: paper

Visual Anomaly Detection in Event Sequence Data
Shunan Guo, Zhuochen Jin, Qing Chen et al. IEEE International Conference on Big Data (BigData), 2019. Cites: paper

Data Resource Profile: Regional healthcare information platform in Halland, Sweden
Awais Ashfaq, Stefan Lönn, Håkan Nilsson et al. International Journal of Epidemiology, 2019. Cites: paper

Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients
Antonin Dauvin, Carolina Donado, Patrik Bächtiger et al. npj Digital Medicine, 2019. Cites: paper

Cited by