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

On Computer-Aided Prognosis of Septic Shock from Vital Signs
Hasan Oğul, Alejandro Baldominos, Tunç Aşuroğlu et al. IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2019. Cites: paper

Publishing Sensitive Trajectory Data Under Enhanced l-Diversity Model
Lin Yao, Xinyu Wang, Xin Wang et al. IEEE International Conference on Mobile Data Management (MDM), 2019. Cites: paper

Sepsis Prediction: An Attention-Based Interpretable Approach
Kourosh T. Baghaei, Shahram Rahimi. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2019. Cites: paper

Using Temporal Feature Aggregation and Gradient Boosting Tree on Missing Data Imputation
Yanni Kang, Xiaoyu Jia, Xiang Li et al. IEEE International Conference on Healthcare Informatics (ICHI), 2019. Cites: paper

XGBoost Imputation for Time Series Data
Xinmeng Zhang, Chao Yan, Cheng Gao et al. IEEE International Conference on Healthcare Informatics (ICHI), 2019. Cites: paper

Patterns of diuretic use in the intensive care unit
Ian Ellis McCoy, Glenn Matthew Chertow, Tara I. Chang. PLoS ONE, 2019. Cites: paper

Defining Admissible Rewards for High Confidence Policy Evaluation
Niranjani Prasad, Barbara Elizabeth Engelhardt, Finale Doshi‐Velez. arXiv (Cornell University), 2019. Cites: paper

GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
Edward De Brouwer, Jaak Simm, Ádám Arany et al. arXiv (Cornell University), 2019. Cites: paper

Toward Precision Medicine in Intensive Care: Leveraging Electronic Health Records and Patient Similarity
Anis Sharafoddini. UWSpace (University of Waterloo), 2019. Cites: paper

Learning and recommending treatments using electronic medical records
Khanh Hung Hoang, Tu Bao Ho. Knowledge-Based Systems, 2019. Cites: paper

Ensemble method–based extraction of medication and related information from clinical texts
Young-Jun Kim, Stéphane M. Meystre. Journal of the American Medical Informatics Association, 2019. Cites: paper

Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods
Fenia Christopoulou, Thy Thy Tran, Sunil Kumar Sahu et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes
Jinmiao Huang, Cesar Osorio, Luke Wicent Sy. Computer Methods and Programs in Biomedicine, 2019. Cites: paper

Enhancing clinical concept extraction with contextual embeddings
Yuqi Si, Jingqi Wang, Hua Xu et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

Learning personalized treatments via IRL
Stav Belogolovsky, Philip Korsunsky, Shie Mannor et al. arXiv (Cornell University), 2019. Cites: paper

Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records
Annelaura Bach Nielsen, Hans‐Christian Thorsen‐Meyer, Kirstine Belling et al. The Lancet Digital Health, 2019. Cites: paper

Étude de nouvelles techniques d’interaction en situation de mobilité avec des lunettes électroniques pour le domaine de la santé
Ilyasse Belkacem. 2019. Cites: paper

Likelihood-Based Adaptive Learning in Stochastic State-Based Models
Peter Vieting, Rodrigo C. de Lamare, Lukas Märtin et al. IEEE Signal Processing Letters, 2019. Cites: paper

Optimizing Sequential Medical Treatments with Auto-Encoding Heuristic Search in POMDPs
Luchen Li, Matthieu Komorowski, A. Aldo Faisal. arXiv (Cornell University), 2019. Cites: paper

Output-Constrained Bayesian Neural Networks
Wanqian Yang, Lars Lorch, Moritz A. Graule et al. arXiv (Cornell University), 2019. Cites: paper

Consensus-based Interpretable Deep Neural Networks with Application to Mortality Prediction
Shaeke Salman, Seyedeh Neelufar Payrovnaziri, Xiuwen Liu et al. arXiv (Cornell University), 2019. Cites: paper

A machine learning approach for predicting urine output after fluid administration
Pei-Chen Lin, Hsu-Cheng Huang, Matthieu Komorowski et al. Computer Methods and Programs in Biomedicine, 2019. Cites: paper

Assessing privacy and quality of synthetic health data
Andrew Yale, Saloni Dash, Ritik Dutta et al. 2019. Cites: paper

Distributed Tensor Decomposition for Large Scale Health Analytics
Huan He, Jette Henderson, Joyce C. Ho. International World Wide Web Conference (WWW), 2019. Cites: paper

Faculty Opinions recommendation of Scalable and accurate deep learning with electronic health records.
Charles Hobson. Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature, 2019. Cites: paper

Improving Medical Code Prediction from Clinical Text via Incorporating Online Knowledge Sources
Tian Bai, Slobodan Vučetić. International World Wide Web Conference (WWW), 2019. Cites: paper

Using a Multi-Task Recurrent Neural Network With Attention Mechanisms to Predict Hospital Mortality of Patients
Ruoxi Yu, Yali Zheng, Ruikai Zhang et al. IEEE Journal of Biomedical and Health Informatics, 2019. Cites: paper

Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
Anna-Lena Popkes, Hiske Overweg, Ari Ercole et al. arXiv (Cornell University), 2019. Cites: paper

The paradox prevails: Outcomes are better in critically ill obese patients regardless of the comorbidity burden
Prakash Acharya, Laxmi Upadhyay, Ahmed Hassaan Qavi et al. Journal of Critical Care, 2019. Cites: paper

ML-Net: multi-label classification of biomedical texts with deep neural networks
Jingcheng Du, Qingyu Chen, Yifan Peng et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery
Xiao Qing Wang, Brenda M. Vincent, Wyndy L. Wiitala et al. BMC Medical Research Methodology, 2019. Cites: paper

VetTag: improving automated veterinary diagnosis coding via large-scale language modeling
Yuhui Zhang, Allen Nie, Ashley M. Zehnder et al. npj Digital Medicine, 2019. Cites: paper

An ensemble of neural models for nested adverse drug events and medication extraction with subwords
Meizhi Ju, Nhung T. H. Nguyen, Makoto Miwa et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining
Jidapa Thadajarassiri, Cansu Şen, Thomas Hartvigsen et al. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2019. Cites: paper

Counterintuitive results from observational data: a case study and discussion
Erik Doty, David J. Stone, Ned McCague et al. BMJ Open, 2019. Cites: paper

Dexmedetomidine versus midazolam and propofol for sedation in critically ill patients: Mining the Medical Information Mart for Intensive Care data
Yiyan Song, Shaowei Gao, Wulin Tan et al. Annals of Translational Medicine, 2019. Cites: paper

Unpacking Prevalence and Dichotomy in qSOFA Parameters: A Step towards Multi-parameter Intelligent Sepsis Prediction in ICU
Nazmus Sakib, Devansh Saxena, Lin He et al. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2019. Cites: paper

Prognostic accuracy of the serum lactate level, the SOFA score and the qSOFA score for mortality among adults with Sepsis
Zhiqiang Liu, Zibo Meng, Yongfeng Li et al. Scandinavian Journal of Trauma Resuscitation and Emergency Medicine, 2019. Cites: paper

A novel GA-ELM model for patient-specific mortality prediction over large-scale lab event data
Gokul S Krishnan, S. Sowmya Kamath. Applied Soft Computing, 2019. Cites: paper

Designing Theory-Driven User-Centric Explainable AI
Danding Wang, Qian Yang, Ashraf Abdul et al. CHI Conference on Human Factors in Computing Systems, 2019. Cites: paper

Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse
Dmitriy Dligach, Majid Afshar, Timothy A. Miller. Journal of the American Medical Informatics Association, 2019. Cites: paper

Temporal-Clustering Invariance in Irregular Healthcare Time Series
Mohammad Taha Bahadori, Zachary C. Lipton. arXiv (Cornell University), 2019. Cites: paper

A machine learning model for predicting ICU readmissions and key risk factors: analysis from a longitudinal health records
Alvaro Ribeiro Botelho Junqueira, Farhaan Mirza, Mirza Mansoor Baig. Health and Technology, 2019. Cites: paper

Cardiac arrest: prediction models in the early phase of hospitalization
Florence Dumas, Wulfran Bougouin, Alain Cariou. Current Opinion in Critical Care, 2019. Cites: paper

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs
Christopher Barton, Uli K. Chettipally, Yifan Zhou et al. Computers in Biology and Medicine, 2019. Cites: paper

A study of deep learning approaches for medication and adverse drug event extraction from clinical text
Qiang Wei, Zongcheng Ji, Zhiheng Li et al. Journal of the American Medical Informatics Association, 2019. Cites: paper

Causality Assessment of Adverse Drug Reaction: Controlling Confounding Induced by Polypharmacy
Tran-Thai Dang, Thanh-Hang Nguyen, Tu-Bao Ho. Current Pharmaceutical Design, 2019. Cites: paper

Data-driven discovery of a novel sepsis pre-shock state predicts impending septic shock in the ICU
Ran Liu, Joseph L. Greenstein, Stephen J. Granite et al. Scientific Reports, 2019. Cites: paper

Machine learning for early prediction of circulatory failure in the intensive care unit
Stephanie L. Hyland, Martin Faltys, Matthias Hüser et al. arXiv (Cornell University), 2019. Cites: paper

Neural transfer learning for assigning diagnosis codes to EMRs
Anthony Rios, Ramakanth Kavuluru. Artificial Intelligence in Medicine, 2019. Cites: paper

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