Publications citing MIMIC-III Waveform Database Matched Subset v1.0

Reinforcement Learning for Clinical Decision Support in Critical Care: Comprehensive Review
Siqi Liu, Kay Choong See, Kee Yuan Ngiam et al. Journal of Medical Internet Research, 2020. Cites: paper

Machine Learning for Precision Health Economics and Outcomes Research (P-HEOR): Conceptual Review of Applications and Next Steps
Yixi Chen, Viktor Chirikov, Xiaocong Li Marston et al. Journal of health economics and outcomes research, 2020. Cites: paper

Fold-stratified cross-validation for unbiased and privacy-preserving federated learning
Romain Bey, Romain Goussault, François Grolleau et al. Journal of the American Medical Informatics Association, 2020. Cites: paper

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients
Lu, MingYu, Zachary Shahn, Daby Sow et al. PubMed Central, 2020. Cites: paper

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment
Mingyu Lu, Zachary Shahn, Daby Sow et al. arXiv (Cornell University), 2020. Cites: paper

Local–Global Memory Neural Network for Medication Prediction
Jun Song, Yueyang Wang, Siliang Tang et al. IEEE Transactions on Neural Networks and Learning Systems, 2020. Cites: paper

Predicting outcome in liver patients admitted to intensive care: A dual-centre non-specialist hospital external validation of the Liver injury and Failure evaluation score
Eleanor de Sausmarez, Paul Crowest, Steve Fry et al. Journal of the Intensive Care Society, 2020. Cites: paper

Imputation of Missing Data in Electronic Health Records Based on Patients’ Similarities
Ali Reza Jazayeri, Ou Stella Liang, Christopher C. Yang. Journal of Healthcare Informatics Research, 2020. Cites: paper

Piloting a model-to-data approach to enable predictive analytics in health care through patient mortality prediction
Timothy R. Bergquist, Yao Yan, Thomas Schaffter et al. Journal of the American Medical Informatics Association, 2020. Cites: paper

Regression of survival data via twin support vector regression
Guangzhi Ma, Xuejing Zhao. Communications in Statistics - Simulation and Computation, 2020. Cites: paper

Validation process of a high‐resolution database in a paediatric intensive care unit—Describing the perpetual patient's validation
Audrey Mathieu, Michaël Sauthier, Philippe A. Jouvet et al. Journal of Evaluation in Clinical Practice, 2020. Cites: paper

Benchmarking big observational health data
Bas Katsma, Jeremy Georges-Filteau. 2020. Cites: paper

Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine, Aviral Kumar, George Tucker et al. arXiv (Cornell University), 2020. Cites: paper

A Feature Optimized Deep Learning Model for Clinical Data Mining
Tianshu Wu, Shuyu Chen, Yingming Tian et al. Chinese Journal of Electronics, 2020. Cites: paper

A Review of Predictive Analytics Solutions for Sepsis Patients
Andrew K. Teng, Adam B Wilcox. Applied Clinical Informatics, 2020. Cites: paper

Development of a Medical Incident Report Corpus with Intention and Factuality Annotation.
Hongkuan Zhang, Ryohei Sasano, Koichi Takeda et al. Language Resources and Evaluation, 2020. Cites: paper

Exploring Transformer Text Generation for Medical Dataset Augmentation.
Ali Amin-Nejad, Julia Ive, Sumithra U. Velupillai. Research Portal (King's College London), 2020. Cites: paper

Identifying Risk Factors for Pressure Injury in Adult Critical Care Patients
Jill Cox, Marilyn E. Schallom, Christy Jung. American Journal of Critical Care, 2020. Cites: paper

In-hospital Mortality Prediction for ICU Patients on Large Healthcare MIMIC Datasets Using Class Imbalance Learning
Lijuan Li, Guangjian Liu. IEEE International Conference on Big Data Analytics (ICBDA), 2020. Cites: paper

Prognostic values of SOFA score, qSOFA score, and LODS score for patients with sepsis
Yonglin Li, Chunjiang Yan, Ziyan Gan et al. Annals of Palliative Medicine, 2020. Cites: paper

Rad-SpatialNet: A Frame-based Resource for Fine-Grained Spatial Relations in Radiology Reports.
Surabhi Datta, Morgan Ulinski, Jordan Godfrey-Stovall et al. PubMed, 2020. Cites: paper

The association between neutrophil-to-lymphocyte count ratio and mortality in septic patients: a retrospective analysis of the MIMIC-III database
Weiyan Ye, Xiaoli Chen, Yongbo Huang et al. Journal of Thoracic Disease, 2020. Cites: paper

Analysis of adult disease characteristics and mortality on MIMIC-III
Zheng Y. Dai, Siru Liu, Jinfa Wu et al. PLoS ONE, 2020. Cites: paper

Cohort selection for clinical trials using multiple instance learning
Hong-Jie Dai, Feng-Duo Wang, Chih‐Wei Chen et al. Journal of Biomedical Informatics, 2020. Cites: paper

[Comparison of four scoring systems for predicting ICU mortality in patients with sepsis].
Chang Hu, Bo Hu, Zhifeng Li et al. PubMed Central, 2020. Cites: paper

Multimodal Neurological Monitoring
Samson Zarbiv, Erica Fagleman, Neha Subhash Dangayach. Cambridge University Press eBooks, 2020. Cites: paper

Evaluation and Improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Ewan Carr, Rebecca Bendayan, Daniel M. Bean et al. medRxiv, 2020. Cites: paper

Data sharing in the era of COVID-19
Christopher V. Cosgriff, Daniel K. Ebner, Leo Anthony Celi. The Lancet Digital Health, 2020. Cites: paper

Incidence and Risk Model Development for Severe Tachypnea Following Terminal Extubation
Corey R. Fehnel, Miguel Ángel Armengol de la Hoz, Leo Anthony Celi et al. CHEST Journal, 2020. Cites: paper

Vital-sign circadian rhythms in patients prior to discharge from an ICU: a retrospective observational analysis of routinely recorded physiological data
Shaun M. Davidson, Mauricio Villarroel, Mirae Harford et al. Critical Care, 2020. Cites: paper

Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision
Dae Hyun Lee, Meliha Yetişgen, Lucy Vanderwende et al. Journal of Biomedical Informatics, 2020. Cites: paper

Harmonized representation learning on dynamic EHR graphs
Dongha Lee, Xiaoqian Jiang, Hwanjo Yu. Journal of Biomedical Informatics, 2020. Cites: paper

AN EARLY PREDICTION AND DIAGNOSIS OF SEPSIS IN INTENSIVE CARE UNITS: AN UNSUPERVİSED MACHINE LEARNING MODEL
Gökhan Silahtaroğlu, Zehra Nur Canbolat. Mugla Journal of Science and Technology, 2020. Cites: paper

Dr. Agent: Clinical predictive model via mimicked second opinions
Junyi Gao, Cao Xiao, Lucas M. Glass et al. Journal of the American Medical Informatics Association, 2020. Cites: paper

Feature engineering with clinical expert knowledge: A case study assessment of machine learning model complexity and performance
Kenneth D. Roe, Vibhu Jawa, Xiaohan Zhang et al. PLoS ONE, 2020. Cites: paper

CHEER: Rich Model Helps Poor Model via Knowledge Infusion
Cao Xiao, Trong Nghia Hoang, Shenda Hong et al. IEEE Transactions on Knowledge and Data Engineering, 2020. Cites: paper

„Machine learning“ in der Anästhesiologie
Julian Sassenscheidt, Bettina Jungwirth, Jens Christian Kubitz. Der Anaesthesist, 2020. Cites: paper

Adversarial Cooperative Imitation Learning for Dynamic Treatment Regimes✱
Lu Wang, Wenchao Yu, Xiaofeng He et al. International World Wide Web Conference (WWW), 2020. Cites: paper

ALPS: Active Learning via Perturbations
Dani Kiyasseh, Tingting Zhu, David Andrew Clifton. arXiv (Cornell University), 2020. Cites: paper

CLOPS: Continual Learning of Physiological Signals
Dani Kiyasseh, Tingting Zhu, David Andrew Clifton. arXiv (Cornell University), 2020. Cites: paper

StageNet: Stage-Aware Neural Networks for Health Risk Prediction
Junyi Gao, Cao Xiao, Yasha Wang et al. International World Wide Web Conference (WWW), 2020. Cites: paper

Text-to-SQL Generation for Question Answering on Electronic Medical Records
Ping Wang, Tian Shi, Chandan K. A. Reddy. International World Wide Web Conference (WWW), 2020. Cites: paper

Toward Optimal Heparin Dosing by Comparing Multiple Machine Learning Methods: Retrospective Study
Longxiang Su, Chun Liu, Dongkai Li et al. JMIR Medical Informatics, 2020. Cites: paper

Harnessing Big Data in Neurocritical Care in the Era of Precision Medicine
Ayham M. Alkhachroum, Kalijah Terilli, Murad Megjhani et al. Current Treatment Options in Neurology, 2020. Cites: paper

LoAdaBoost: Loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data
Huang Li, Yifeng Yin, Zeng Fu et al. PLoS ONE, 2020. Cites: paper

Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts
Steven Jiang, Weiyi Wu, Naofumi Tomita et al. arXiv (Cornell University), 2020. Cites: paper

Science Without Conscience Is but the Ruin of the Soul: The Ethics of Big Data and Artificial Intelligence in Perioperative Medicine
Cecilia Canales, Christine Lee, Maxime P. Cannesson. Anesthesia & Analgesia, 2020. Cites: paper

A Revised Point-to-Point Calibration Approach with Adaptive Errors Correction to Weaken Initial Sensitivity of Cuff-Less Blood Pressure Estimation
Jiang Shao, Ping An Shi, Sijung Hu et al. Sensors, 2020. Cites: paper

Uncertainty estimation for classification and risk prediction in medical settings.
Lotta Meijerink, Giovanni Cinà, Michele Tonutti. arXiv (Cornell University), 2020. Cites: paper

Uncertainty estimation for classification and risk prediction on medical tabular data
Lotta Meijerink, Giovanni Cinà, Michele Tonutti. arXiv (Cornell University), 2020. Cites: paper

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