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

Big data and machine learning in critical care: Opportunities for collaborative research
Antonio Núñez Reiz, Fernando Martínez‐Sagasti, Manuel Álvarez González et al. Medicina Intensiva, 2018. Cites: paper

An Automated System for Identifying Alcohol Use Status from Clinical Text
Hadeel Alzoubi, Naeem Ramzan, Raid Alzubi et al. International Conference on Computing, Electronics & Communications Engineering (iCCECE), 2018. Cites: paper

Prolonged dexmedetomidine infusion in critically ill adult patients: a retrospective analysis of a large clinical database Multiparameter Intelligent Monitoring in Intensive Care III
Yue Zhao, Huaqiang Zhou, Wulin Tan et al. Annals of Translational Medicine, 2018. Cites: paper

Serum uric acid on admission cannot predict long-term outcome of critically ill patients: a retrospective cohort study
Qinchang Chen, Kai Huang, Lingling Li et al. Therapeutics and Clinical Risk Management, 2018. Cites: paper

Transfer Learning for Entity Recognition of Novel Classes
Juan Diego Rodríguez, Caldwell Adam, Alexander Liu. International Conference on Computational Linguistics, 2018. Cites: paper

Anesthesia research in the artificial intelligence era
Hyung‐Chul Lee, Chul-Woo Jung. Anesthesia and Pain Medicine, 2018. Cites: paper

Risk of health morbidity for the uninsured: 10-year evidence from a large hospital center in Boston, Massachusetts
Zhaoyi Chen, Jae S. Min, Jiang Bian et al. International Journal for Quality in Health Care, 2018. Cites: paper

Open data informatics and data repurposing for IBD
Vivek Ashok Rudrapatna, Atul Janardhan Butte. Nature Reviews Gastroenterology & Hepatology, 2018. Cites: paper

Um Modelo de Predição de Mortalidade em Unidades de Terapia Intensiva Baseado em Deep Learning
Diogo Schmidt, Denise Bandeira da Silva, Cristiano André da Costa et al. 2018. Cites: paper

A Treatment Engine by Predicting Next-Period Prescriptions
Bo Jin, Haoyu Yang, Leilei Sun et al. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
Mengying Sun, Fengyi Tang, Jinfeng Yi et al. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

Learning Tasks for Multitask Learning
Harini Suresh, Jen J. Gong, John V. Guttag. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

RAIM
Yanbo Xu, Siddharth Biswal, Shriprasad R. Deshpande et al. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation
Lu Wang, Wei Zhang, Xiaofeng He et al. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018. Cites: paper

High Serum Iron level is Associated with Increased Mortality in Patients with Sepsis
Peng Lan, Kong-Han Pan, Shuojia Wang et al. Scientific Reports, 2018. Cites: paper

Predictive accuracy of serum total calcium for both critically high and critically low ionized calcium in critical illness
Zhi‐De Hu, Yuan‐Lan Huang, Meiying Wang et al. Journal of Clinical Laboratory Analysis, 2018. Cites: paper

Cause-Effect Deep Information Bottleneck For Incomplete Covariates
Sonali Parbhoo, Mario Wieser, Volker Röth. arXiv (Cornell University), 2018. Cites: paper

Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates
Sonali Parbhoo, Mario Wieser, Aleksander Wieczorek et al. arXiv (Cornell University), 2018. Cites: paper

Early hospital mortality prediction using vital signals
Reza Sadeghi, Tanvi Banerjee, William Romine. Smart Health, 2018. Cites: paper

Data collection and research with MargheritaTre
Stefano Finazzi, Giulia Mandelli, Elena Garbero et al. Physiological Measurement, 2018. Cites: paper

Time-related association between fluid balance and mortality in sepsis patients: interaction between fluid balance and haemodynamics
Yanfei Shen, Weizhe Ru, Xinmei Huang et al. Scientific Reports, 2018. Cites: paper

Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks
Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig et al. arXiv (Cornell University), 2018. Cites: paper

Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
Zhengping Che, Sanjay Purushotham, Guangyu Li et al. International Conference on Machine Learning, 2018. Cites: paper

Patient representation learning and interpretable evaluation using clinical notes
Madhumita Sushil, Simon Šuster, Kim Luyckx et al. Journal of Biomedical Informatics, 2018. Cites: paper

Serum anion gap on admission predicts intensive care unit mortality in patients with aortic aneurysm
Qinchang Chen, Qingui Chen, Lingling Li et al. Experimental and Therapeutic Medicine, 2018. Cites: paper

A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU
Rongmei Lin, Matthew D. Stanley, Mohammad M. Ghassemi et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Arteriosclerosis Diagnosis Based on Support Vector Machine
Junjun Pan, Yue Zhang. International Conference on Information Science and Control Engineering, 2018. Cites: paper

Early Prediction of Sepsis in EMR Records Using Traditional ML Techniques and Deep Learning LSTM Networks
Mohammed Saqib, Ying Sha, May Dongmei Wang. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Fuzzy Modeling for Predicting Patient Survival Rate in ICU with AKI
Andre D. Silva, Clara C. Correia, Cátia M. Salgado et al. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018. Cites: paper

Joint Learning of Phenotypes and Diagnosis-Medication Correspondence via Hidden Interaction Tensor Factorization
Kejing Yin, William K. Cheung, Yang Liu et al. International Joint Conference on Artificial Intelligence, 2018. Cites: paper

Predicting Mortality in the Surgical Intensive Care Unit Using Artificial Intelligence and Natural Language Processing of Physician Documentation
Joshua P. Parreco, Antonio E. Hidalgo, Robert A. Kozol et al. The American Surgeon, 2018. Cites: paper

Prediction of ICU Readmissions Using Data at Patient Discharge
Arash Pakbin, Parvez Rafi, Nate Hurley et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Predictive Value of Prothrombin Time for All-cause Mortality in Acute Myocardial Infarction Patients
Xurong Wang, Runge Chen, Ye Li et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018. Cites: paper

Modeling Mistrust in End-of-Life Care
Willie Boag, Harini Suresh, Leo Anthony Celi et al. arXiv (Cornell University), 2018. Cites: paper

Boosting Clinical Decision-making: Machine Learning for Intensive Care Unit Discharge
Christopher V. Cosgriff, Leo Anthony Celi, Christopher Martin Sauer. Annals of the American Thoracic Society, 2018. Cites: paper

CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital
Richard Jackson, Ismail Emre Kartoglu, Asha Agrawal et al. BMC Medical Informatics and Decision Making, 2018. Cites: paper

Mapping Unparalleled Clinical Professional and Consumer Languages with Embedding Alignment
Wei‐Hung Weng, Peter Szolovits B. arXiv (Cornell University), 2018. Cites: paper

Finding Similar Patient Subpopulations in the ICU Using Laboratory Test Ordering Patterns
Anis Sharafoddini, Joel A. Dubin, Joon Lee. International Conference on Bioinformatics and Biomedical Science (ICBBS), 2018. Cites: paper

Countdown Regression: Sharp and Calibrated Survival Predictions
Anand Avati, Tony Duan, Sharon Zhou et al. arXiv (Cornell University), 2018. Cites: paper

Personalized Medication Dosing Using Volatile Data Streams.
Mohammad M. Ghassemi, Tuka Alhanai, Michael Brandon Westover et al. National Conference on Artificial Intelligence, 2018. Cites: paper

The challenge of local consent requirements for global critical care databases
Stuart McLennan, David Shaw, Leo Anthony Celi. Intensive Care Medicine, 2018. Cites: paper

Health information technology: promise and progress
Matt Wimble, Gondy Leroy A. Health Systems, 2018. Cites: paper

Sentiment in nursing notes as an indicator of out-of-hospital mortality in intensive care patients
Ian Waudby-Smith, Nam Tran, Joel A. Dubin et al. PLoS ONE, 2018. Cites: paper

Benchmarking deep learning models on large healthcare datasets
Sanjay Purushotham, Chuizheng Meng, Zhengping Che et al. Journal of Biomedical Informatics, 2018. Cites: paper

Modeling asynchronous event sequences with RNNs
Stephen Wu, Sijia Liu, Sunghwan Sohn et al. Journal of Biomedical Informatics, 2018. Cites: paper

Predictive modeling in urgent care: a comparative study of machine learning approaches
Fengyi Tang, Cao Xiao, Fei Wang et al. JAMIA Open, 2018. Cites: paper

A Hybrid Method for Normalization of Medical Concepts in Clinical Narrative
Yen-Fu Luo, Weiyi Sun, Anna Rumshisky. IEEE International Conference on Healthcare Informatics (ICHI), 2018. Cites: paper

Global Model Interpretation Via Recursive Partitioning
Chengliang Yang, Anand Rangarajan, Sanjay Ranka. IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2018. Cites: paper

Novel Approach to Predict Hospital Readmissions Using Feature Selection from Unstructured Data with Class Imbalance
Arun Thotapalli Sundararaman, Srinivasan Valady Ramanathan, Ramprasad Thati. Big Data Research, 2018. Cites: paper

Pattern Similarity in Time Interval Sequences
Luca Bonomi, Xiaoqian Jiang. IEEE International Conference on Healthcare Informatics (ICHI), 2018. Cites: paper

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