Cited by
MIMIC-III Waveform Database Matched Subset (v1.0)
7929 publications cite any version of this project or its primary paper, newest first.
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Unsupervised Machine learning to subtype Sepsis-Associated Acute Kidney Injury
Kumardeep Chaudhary, Áine Duffy, Priti Poojary et al. bioRxiv (Cold Spring Harbor Laboratory), 2018. Cites: paper -
HeteroMed
Anahita Hosseini, Ting Chen, Wenjun Wu et al. ACM International Conference on Information and Knowledge Management (CIKM), 2018. Cites: paper -
Ontop-temporal
Elem Güzel Kalaycı, Guohui Xiao, Vladislav Ryzhikov et al. ACM International Conference on Information and Knowledge Management (CIKM), 2018. Cites: paper -
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation
Marzyeh Ghassemi, Mahima Pushkarna, James Wexler et al. arXiv (Cornell University), 2018. Cites: paper -
Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients
Max Taggart, Wendy W. Chapman, Benjamin Adam Steinberg et al. JAMA Network Open, 2018. Cites: paper -
Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital
Christopher Martin Sauer, Jinghui Dong, Leo Anthony Celi et al. Cancer Research and Treatment, 2018. Cites: paper -
The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care
Matthieu Komorowski, Leo Anthony Celi, Omar Badawi et al. Nature Medicine, 2018. Cites: paper -
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks
Jinsung Yoon, William R. Zame, Mihaela van der Schaar. IEEE Transactions on Biomedical Engineering, 2018. Cites: paper -
Handling Missing Values in Multivariate Time Series Classification
Julia Friend, Alec Hauck, Sruthi Kurada et al. IEEE MIT Undergraduate Research Technology Conference (URTC), 2018. Cites: paper -
Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts
Ary Serpa Neto, Rodrigo Octávio Deliberato, Alistair E. W. Johnson et al. Intensive Care Medicine, 2018. Cites: paper -
Deep learning facilitates rapid classification of human and veterinary clinical narratives
Arturo López Pineda, Oliver J. Bear Don’t Walk, Guhan Ram Venkataraman et al. bioRxiv (Cold Spring Harbor Laboratory), 2018. Cites: paper -
Impact of Mean Arterial Pressure Fluctuation on Mortality in Critically Ill Patients
Ya Gao, Qinfen Wang, Jiamei Li et al. Critical Care Medicine, 2018. Cites: paper -
Towards automated clinical coding
Finneas J. R. Catling, Georgios Spithourakis, Sebastian Riedel. International Journal of Medical Informatics, 2018. Cites: paper -
Automated ICD-9-CM medical coding of diabetic patient's clinical reports
Vitor Pereira, Sérgio Matos, José Luís Oliveira. International Conference on Data Science, E-Learning and Information Systems (DATA), 2018. Cites: paper -
Identification of Disease States for Trauma Patients using Commonly Available Hospital Data
Mahnaz Koupaee, Yuanyang Zhang, Tie Bo Wu et al. IEEE International Conference on Computational Advances in Bio and Medical Sciences, 2018. Cites: paper -
Impact of Intensive Care Unit Discharge Delays on Patient Outcomes: A Retrospective Cohort Study
Somnath Bose, Alistair E. W. Johnson, Ari L. Moskowitz et al. Journal of Intensive Care Medicine, 2018. Cites: paper -
Life Model: A novel representation of life-long temporal sequences in health predictive analytics
Alireza Manashty, Janet Light. Future Generation Computer Systems, 2018. Cites: paper -
Stockwell Transform Detector For Photoplethysmography Signal Segmentation
Victoria S. Marks, Christopher L. Felton, Robert W. Techentin et al. Asilomar Conference on Signals, Systems and Computers (ACSSC), 2018. Cites: paper -
Can Photoplethysmography Replace Arterial Blood Pressure in the Assessment of Blood Pressure?
Gloria Martínez, Newton Howard, Derek Abbott et al. Journal of Clinical Medicine, 2018. Cites: paper -
Machine learning for real-time prediction of complications in critical care: a retrospective study
Alexander Meyer, Dina Zverinski, Boris Pfahringer et al. The Lancet Respiratory Medicine, 2018. Cites: paper -
C-LACE2: computational risk assessment tool for 30-day post hospital discharge mortality
Janusz Wojtusiak, Eman Elashkar, Reyhaneh Mogharab Nia. Health and Technology, 2018. Cites: paper -
Effectiveness of sodium bicarbonate infusion on mortality in septic patients with metabolic acidosis
Zhongheng Zhang, Carlie Zhu, Lei Mo et al. Intensive Care Medicine, 2018. Cites: paper -
Concept acquisition and improved in-database similarity analysis for medical data
Ingmar Wiese, Nicole S. Sarna, Lena Wiese et al. Distributed and Parallel Databases, 2018. Cites: paper -
A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis
Javier E. García-Gallo, Nelson Javier Fonseca-Ruiz, Leo Anthony Celi et al. Medicina Intensiva, 2018. Cites: paper -
Spline-Based Probability Calibration
Brian Lucena. arXiv (Cornell University), 2018. Cites: paper -
Understanding Behavior of Clinical Models under Domain Shifts
Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri. arXiv (Cornell University), 2018. Cites: paper -
What Can We Learn about Fall Risk Factors from EHR Nursing Notes? A Text Mining Study
Ragnhildur I. Bjarnadóttir, Robert James Lucero. eGEMs (Generating Evidence & Methods to improve patient outcomes), 2018. Cites: paper -
A Composite and Wearable Sensor Kit for Location-Aware Healthcare Monitoring and Real-Time Trauma Scoring for Survival Prediction
Amit Walinjkar. Applied System Innovation, 2018. Cites: paper -
Red blood cell distribution width predicts long-term outcomes in sepsis patients admitted to the intensive care unit
Yanqiu Han, Lei Zhang, Yan Li et al. Clinica Chimica Acta, 2018. Cites: paper -
A comparison of word embeddings for the biomedical natural language processing
Yanshan Wang, Sijia Liu, Naveed Afzal et al. Journal of Biomedical Informatics, 2018. Cites: paper -
The eICU Collaborative Research Database, a freely available multi-center database for critical care research
Tom Pollard, Alistair E. W. Johnson, Jesse D. Raffa et al. Scientific Data, 2018. Cites: paper -
Hypertension Assessment via ECG and PPG Signals: An Evaluation Using MIMIC Database
Yongbo Liang, Zhencheng Chen, Rabab Kreidieh Ward et al. Diagnostics, 2018. Cites: paper -
Predicting ICU readmission using grouped physiological and medication trends
Ye Xue, Diego Klabjan, Yuan Luo. Artificial Intelligence in Medicine, 2018. Cites: paper -
Rethinking Data Sharing at the Dawn of a Health Data Economy: A Viewpoint
Chunlei Tang, Joseph Michael Plasek, David Westfall Bates. Journal of Medical Internet Research, 2018. Cites: paper -
Neutrophil-lymphocyte ratio is associated with all-cause mortality among critically ill patients with acute kidney injury
Lailai Fan, Yi jun Wang, Cunjin Nan et al. Clinica Chimica Acta, 2018. Cites: paper -
A new prediction model for assessing the clinical outcomes of ICU patients with community-acquired pneumonia: a decision tree analysis
Shufang Zhang, Kai Zhang, Yang Yu et al. Annals of Medicine, 2018. Cites: paper -
Prompt admission to intensive care is associated with improved survival in patients with severe sepsis and/or septic shock
Qiang Li, Jiajiong Wang, Guomin Liu et al. Journal of International Medical Research, 2018. Cites: paper -
Identifying the relationship between unstable vital signs and intensive care unit (ICU) readmissions: an analysis of 10-year of hospital ICU readmissions
Abdulla Ubaid, Farhaan Mirza, Mirza Mansoor Baig et al. Health and Technology, 2018. Cites: paper -
Association of Sex With Clinical Outcome in Critically Ill Sepsis Patients: A Retrospective Analysis of the Large Clinical Database MIMIC-III
Jinghong Xu, Tong Li, Jiyou Yao et al. Shock, 2018. Cites: paper -
New Methods for Improving Accuracy in Three Distinct Predictive Modeling Problems
Yingying Xu. UWSpace (University of Waterloo), 2018. Cites: paper -
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks
Jeeheh Oh, Jiaxuan Wang, Jenna Wiens. PubMed, 2018. Cites: paper -
Lessons from Natural Language Inference in the Clinical Domain
Alexey Romanov, Chaitanya Shivade. arXiv (Cornell University), 2018. Cites: paper -
Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis
Kristen Severson, Laura Ritter-Cox, Jesse D. Raffa et al. Journal of Intensive Care Medicine, 2018. Cites: paper -
Doccurate: A Curation-Based Approach for Clinical Text Visualization
Nicole Sultanum, Devin Singh, Michael Brudno et al. IEEE Transactions on Visualization and Computer Graphics, 2018. Cites: paper -
Visual Progression Analysis of Event Sequence Data
Shunan Guo, Zhuochen Jin, David Gotz et al. IEEE Transactions on Visualization and Computer Graphics, 2018. Cites: paper -
Development of a personalized diagnostic model for kidney stone disease tailored to acute care by integrating large clinical, demographics and laboratory data: the diagnostic acute care algorithm - kidney stones (DACA-KS)
Zhaoyi Chen, Victoria Yvonne Bird, Rupam Ruchi et al. BMC Medical Informatics and Decision Making, 2018. Cites: paper -
High 28-day mortality in critically ill patients with sepsis and concomitant active cancer
Yong-gang Wang, Jiancang Zhou, Kang-song Wu. Journal of International Medical Research, 2018. Cites: paper -
Learning to Write Notes in Electronic Health Records
Peter J. Liu. arXiv (Cornell University), 2018. Cites: paper -
Word-Level Loss Extensions for Neural Temporal Relation Classification
Artuur M. Leeuwenberg, Marie‐Francine Moens. Lirias, 2018. Cites: paper -
A Concise Temporal Data Representation Model for Prediction in Biomedical Wearable Devices
Alireza Manashty, Janet Light Thompson, Hamid Soleimani. IEEE Internet of Things Journal, 2018. Cites: paper
Citation data from OpenAlex, updated weekly. Papers that use the project without citing it may be missing.