Cited by
MIMIC-III Waveform Database (v1.0)
7936 publications cite any version of this project or its primary paper, newest first.
-
EHR phenotyping via jointly embedding medical concepts and words into a unified vector space
Tian Bai, Ashis Kumar Chanda, Brian Lee Egleston et al. BMC Medical Informatics and Decision Making, 2018. Cites: paper -
How to start a company in five (not so) easy steps
Michael R Stonebraker. ACM eBooks, 2018. Cites: paper -
Identification of subclasses of sepsis that showed different clinical outcomes and responses to amount of fluid resuscitation: a latent profile analysis
Zhongheng Zhang, Gensheng Zhang, Hemant Goyal et al. Critical Care, 2018. Cites: paper -
In-memory, horizontal, and transactional: the H-store OLTP DBMS project
Andy Pavlo. ACM eBooks, 2018. Cites: paper -
Leadership and advocacy
Philip A. Bernstein. ACM eBooks, 2018. Cites: paper -
Make it happen: the life of Michael Stonebraker
Samuel R. Madden. ACM eBooks, 2018. Cites: paper -
Mike Stonebraker speaks out: an interview
Marianne Winslett. ACM eBooks, 2018. Cites: paper -
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
Citation data from OpenAlex, updated weekly. Papers that use the project without citing it may be missing.