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

OLTP through the looking glass, and what we found there
Stavros Harizopoulos, Daniel J. Abadi, Samuel R. Madden et al. ACM eBooks, 2018. Cites: paper

Perspectives: the 2014 ACM turing award
James Russell Hamilton. ACM eBooks, 2018. Cites: paper

Research contributions of Mike Stonebraker: an overview
Samuel R. Madden. ACM eBooks, 2018. Cites: paper

Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data
Zakhriya Alhassan, David Budgen, Riyad Alshammari et al. International Conference on Machine Learning and Applications, 2018. Cites: paper

SynthNotes: A Generator Framework for High-volume, High-fidelity Synthetic Mental Health Notes
Edmon Begoli, Kris Brown, Sudarshan Srinivas et al. IEEE International Conference on Big Data (BigData), 2018. Cites: paper

The BigDAWG codeline
Vijay N. Gadepally. ACM eBooks, 2018. Cites: paper

The BigDAWG polystore system
Tim Mattson, Jennie Rogers, Aaron J. Elmore. ACM eBooks, 2018. Cites: paper

The commercial Ingres codeline
Paul Butterworth, Fred Carter. ACM eBooks, 2018. Cites: paper

The design and implementation of INGRES
Michael R Stonebraker, Eugene Wong, Peter Kreps et al. ACM eBooks, 2018. Cites: paper

The end of an architectural era: it's time for a complete rewrite
Michael R Stonebraker, Samuel R. Madden, Daniel J. Abadi et al. ACM eBooks, 2018. Cites: paper

The implementation of POSTGRES
Michael R Stonebraker, Lawrence A. Rowe, Michael Hirohama. ACM eBooks, 2018. Cites: paper

The later Ingres years
Michael J. Carey. ACM eBooks, 2018. Cites: paper

The relational database management systems genealogy
Felix Naumann. ACM eBooks, 2018. Cites: paper

Where good ideas come from and how to exploit them
Michael R Stonebraker. ACM eBooks, 2018. Cites: paper

Where we have failed
Michael R Stonebraker. ACM eBooks, 2018. Cites: paper

LoAdaBoost:Loss-Based AdaBoost Federated Machine Learning on medical Data
Huang Li, Yifeng Yin, Zeng Fu et al. arXiv (Cornell University), 2018. Cites: paper

Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation
Bret A. Nestor, Matthew B. A. McDermott, Geeticka Chauhan et al. arXiv (Cornell University), 2018. Cites: paper

Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning
Mengqi Jin, Mohammad Taha Bahadori, Aaron Colak et al. arXiv (Cornell University), 2018. Cites: paper

Leveraging Clinical Time-Series Data for Prediction: A Cautionary Tale
Eli Sherman, Hitinder Singh Gurm, Ulysses J. Balis et al. PubMed Central, 2018. Cites: paper

The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database
Angelina Prima Kurniati, Eric Rojas, David Hogg et al. Health Informatics Journal, 2018. Cites: paper

Estimating Causal Effects With Partial Covariates For Clinical Interpretability
Sonali Parbhoo, Mario Wieser, Volker Röth. arXiv (Cornell University), 2018. Cites: paper

Application of Clinical Concept Embeddings for Heart Failure Prediction in UK EHR data
Spiros Denaxas, Pontus Stenetorp, Sebastian Riedel et al. arXiv (Cornell University), 2018. Cites: paper

Model-Based Reinforcement Learning for Sepsis Treatment
Aniruddh Raghu, Matthieu Komorowski, Sumeetpal Sidhu Singh. arXiv (Cornell University), 2018. Cites: paper

Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Xiangan Liu, Keyang Xu, Pengtao Xie et al. arXiv (Cornell University), 2018. Cites: paper

Employing Domain Indexes to Efficiently Query Medical Data From Multiple Repositories
Paulo H. Oliveira, Lucas C. Scabora, Mirela T. Cazzolato et al. IEEE Journal of Biomedical and Health Informatics, 2018. Cites: paper

Deep learning algorithms to identify documentation of serious illness conversations during intensive care unit admissions
Alex Chan, Isabel Chien, Edward T. Moseley et al. Palliative Medicine, 2018. Cites: paper

Optimal intensive care outcome prediction over time using machine learning
Christopher Meiring, Abhishek Dixit, Steve K. Harris et al. PLoS ONE, 2018. Cites: paper

Embedding Electronic Health Records for Clinical Information Retrieval
Xing Wei, Carsten Eickhoff. arXiv (Cornell University), 2018. Cites: paper

Few-shot Learning for Named Entity Recognition in Medical Text
Hofer, Maximilian, Andrey Kormilitzin, Paul W. Goldberg et al. arXiv (Cornell University), 2018. Cites: paper

Improving counterfactual reasoning with kernelised dynamic mixing models
Sonali Parbhoo, Omer Gottesman, Andrew Slavin Ross et al. PLoS ONE, 2018. Cites: paper

Assessment of Intensive Care Unit Laboratory Values That Differ From Reference Ranges and Association With Patient Mortality and Length of Stay
Patrick D. Tyler, Hao Du, Mengling Feng et al. JAMA Network Open, 2018. Cites: paper

Post-extrasystolic characteristics in the arterial blood pressure waveform are associated with right ventricular dysfunction in intensive care patients
Simon Tilma Vistisen, Benjamin Moody, Leo Anthony Celi et al. Journal of Clinical Monitoring and Computing, 2018. Cites: paper

A method for harmonization of clinical abbreviation and acronym sense inventories
Lisa Grossman Liu, Elliot G. Mitchell, George M. Hripcsak et al. Journal of Biomedical Informatics, 2018. Cites: paper

International normalized ratio on admission predicts the 90‑day mortality of critically ill patients undergoing endarterectomy
Langping Tan, Yi‐Biao Ye, Yue Zhu et al. Experimental and Therapeutic Medicine, 2018. Cites: paper

Medical code prediction with multi-view convolution and description-regularized label-dependent attention
Najmeh Sadoughi, Greg P. Finley, James Fone et al. arXiv (Cornell University), 2018. Cites: paper

Prognostic nomogram for acute pancreatitis patients: An analysis of publicly electronic healthcare records in intensive care unit
Xihui Jiang, Zhengyan Su, Ya Wang et al. Journal of Critical Care, 2018. Cites: paper

Comparison of Approaches to the identification of Symptom Burden in Hemodialysis Patients Utilizing Electronic Health Records
Lili Chan, Kelly H. Beers, Kinsuk Chauhan et al. bioRxiv (Cold Spring Harbor Laboratory), 2018. Cites: paper

Prevalence and Nature of Financial Considerations Documented in Narrative Clinical Records in Intensive Care Units
Deborah D. Gordon, Ihsaan H. Patel, Amelia M. Pellegrini et al. JAMA Network Open, 2018. Cites: paper

An Optimal Policy for Patient Laboratory Tests in Intensive Care Units
Li-Fang Cheng, Niranjani Prasad, Barbara Elizabeth Engelhardt. Pacific Symposium on Biocomputing (PSB), 2018. Cites: paper

Developing a healthcare dataset information resource (DIR) based on Semantic Web
Jingyi Shi, Mingna Zheng, Lixia Yao et al. BMC Medical Genomics, 2018. Cites: paper

Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit
Weitong Chen, Sen Wang, Guodong Long et al. Proceedings, 2018. Cites: paper

“Flying blind” or “in plain sight”?
Veit Sandfort. Journal of Emergency and Critical Care Medicine, 2018. Cites: paper

Machine learning in critical care: state-of-the-art and a sepsis case study
Alfredo Vellido, Vicent J. Ribas, Carles Morales et al. BioMedical Engineering OnLine, 2018. Cites: paper

Merkle-Tree Based Approach for Ensuring Integrity of Electronic Medical Records
Brihat Sharma, Chandra N. Sekharan, Fanyu Zuo. IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2018. Cites: paper

Multimodal Machine Learning for Automated ICD Coding
Keyang Xu, Mike Lam, Jingzhi Pang et al. arXiv (Cornell University), 2018. Cites: paper

Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states
Rihui Ou, Deborshee Sen, Alexander L. Young et al. arXiv (Cornell University), 2018. Cites: paper

Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification
Yongbo Liang, Zhencheng Chen, Rabab Kreidieh Ward et al. Biosensors, 2018. Cites: paper

Artificial Intelligence and Deep Learning in Ophthalmology
Daniel Shu Wei Ting, Louis Robert Pasquale, Lily Peng et al. Springer eBooks, 2018. Cites: paper

Synthesizing electronic health records using improved generative adversarial networks
Mrinal Kanti Baowaly, Chia-Ching Lin, Chao-Lin Liu et al. Journal of the American Medical Informatics Association, 2018. Cites: paper

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
Sumithra U. Velupillai, Hanna Suominen, Maria Liakata et al. Journal of Biomedical Informatics, 2018. Cites: paper

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