Publications citing MIMIC-III Waveform Database v1.0

Attention is not Explanation
Sarthak Jain, Byron Wallace. arXiv (Cornell University), 2019. Cites: paper

Interpretable Structure-aware Document Encoders with Hierarchical Attention
Khalil Mrini, Claudiu Musat, Michael Baeriswyl et al. arXiv (Cornell University), 2019. Cites: paper

A quantitative exploration of gastrointestinal bleeding in intensive care unit patients
Patrick C. Eschenfeldt, Chin Hur. PLoS ONE, 2019. Cites: paper

Outcome-Based Critical Result Thresholds in the Adult Patient Population
Eng Hooi Tan, Zhutian Yang, Yingda Li et al. American Journal of Clinical Pathology, 2019. Cites: paper

Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children: A single center pilot study
Sam Ghazal, Michaël Sauthier, David Brossier et al. PLoS ONE, 2019. Cites: paper

Learning latent variable models : efficient algorithms and applications
Matteo Ruffini. 2019. Cites: paper

Predicting tachycardia as a surrogate for instability in the intensive care unit
Joo Heung Yoon, Liuquan Mu, Lujie Chen et al. Journal of Clinical Monitoring and Computing, 2019. Cites: paper

Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patients
Daniele Ramazzotti, Peter F. Clardy, Leo Anthony Celi et al. PLoS ONE, 2019. Cites: paper

An attention based deep learning model of clinical events in the intensive care unit
Deepak A. Kaji, John R. Zech, Jun Kim et al. PLoS ONE, 2019. Cites: paper

Hierarchical patient-centric caregiver network method for clinical outcomes study
Yoonyoung Park, Panagiotis D. Karampourniotis, Issa Sylla et al. PLoS ONE, 2019. Cites: paper

Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients
Jacob S. Calvert, Nicholas Saber, Jana L. Hoffman et al. Diagnostics, 2019. Cites: paper

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning
Benjamin Shickel, Tyler John Loftus, Lasith Adhikari et al. Scientific Reports, 2019. Cites: paper

Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model
Ke Lin, Yonghua Hu, Guilan Kong. International Journal of Medical Informatics, 2019. Cites: paper

Unsupervised concept extraction from clinical text through semantic composition
Stéphan Tulkens, Simon Šuster, Walter M. P. Daelemans. Journal of Biomedical Informatics, 2019. Cites: paper

Does the "Artificial Intelligence Clinician" learn optimal treatment strategies for sepsis in intensive care?
Russell Bradford, Chris Sangwin, Supreeth Prajwal Shashikumar et al. arXiv (Cornell University), 2019. Cites: paper

Description of Clinical Characteristics of VAP Patients in MIMIC Database
Qingqing Liu, Jin Yang, Jun Zhang et al. Frontiers in Pharmacology, 2019. Cites: paper

Can AI Help Reduce Disparities in General Medical and Mental Health Care?
Irene Y. Chen, Peter Szolovits B, Marzyeh Ghassemi. The AMA Journal of Ethic, 2019. Cites: paper

CASCADENET: An LSTM Based Deep Learning Model for Automated ICD-10 Coding
Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri et al. Lecture notes in networks and systems, 2019. Cites: paper

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders
Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar. arXiv (Cornell University), 2019. Cites: paper

Attention-Based Deep Learning System for Negation and Assertion Detection in Clinical Notes
Long Chen. International Journal of Artificial Intelligence & Applications, 2019. Cites: paper

Data Science for Child Health
Tellen D. Bennett, Tiffany J. Callahan, James Aaron Feinstein et al. The Journal of Pediatrics, 2019. Cites: paper

Dynamic Measurement Scheduling for Event Forecasting using Deep RL
Chun‐Hao Chang, Mai, Mingjie, Anna Goldenberg. arXiv (Cornell University), 2019. Cites: paper

Machine Learning in Health Care: A Critical Appraisal of Challenges and Opportunities
Mark Sendak, Michael C. Gao, Marshall Nichols et al. eGEMs (Generating Evidence & Methods to improve patient outcomes), 2019. Cites: paper

MIMIC-CXR: A large publicly available database of labeled chest radiographs
Alistair E. W. Johnson, Tom Pollard, Seth J. Berkowitz et al. arXiv (Cornell University), 2019. Cites: paper

STAR: Statistical Tests with Auditable Results
Sacha Servan-Schreiber, Olga Ohrimenko, Tim Kraska et al. arXiv (Cornell University), 2019. Cites: paper

Gromov-Wasserstein Learning for Graph Matching and Node Embedding
Hongteng Xu, Dixin Luo, Hongyuan Zha B et al. arXiv (Cornell University), 2019. Cites: paper

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning
Xuefeng Peng, Yi Ding, David Wihl et al. Europe PMC (PubMed Central), 2019. Cites: paper

Multivariate Sequential Analytics for Treatment Trajectory Forecasting
William W.Y. Hsu, Jim Warren, Patricia Riddle. Australasian Computer Science Week Multiconference (ACSW), 2019. Cites: paper

Early diuretic use and mortality in critically ill patients with vasopressor support: a propensity score-matching analysis
Yanfei Shen, Weimin Zhang, Yong Shen. Critical Care, 2019. Cites: paper

A review of big data applications of physiological signal data
Christina Orphanidou. Biophysical Reviews, 2019. Cites: paper

A New Insight Into Missing Data in Intensive Care Unit Patient Profiles: Observational Study
Anis Sharafoddini, Joel A. Dubin, David M. Maslove et al. JMIR Medical Informatics, 2019. Cites: paper

Prognostic value of international normalized ratio to albumin ratio among critically ill patients with cirrhosis
Feng Gao, Mengxing Cai, Miao-Tong Lin et al. European Journal of Gastroenterology & Hepatology, 2019. Cites: paper

Quantifying risk factors in medical reports with a context-aware linear model
Piotr Przybyła, Austin J. Brockmeier, Sophia Ananiadou. Journal of the American Medical Informatics Association, 2019. Cites: paper

Evaluating the quality of word representation models for unstructured clinical Text based ICU mortality prediction
Gokul S Krishnan, S. Sowmya Kamath. International Conference on Distributed Computing and Networking (ICDCN), 2019. Cites: paper

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Chen Lin, Timothy A. Miller, Dmitriy Dligach et al. Clinical Natural Language Processing Workshop (ClinicalNLP), 2019. Cites: paper

A Benchmark Corpus of English Misspellings and a Minimally-supervised Model for Spelling Correction
Michael Flor, Michael Fried, Alla Rozovskaya. Workshop on Innovative Use of NLP for Building Educational Applications, 2019. Cites: paper

Abordagem I3VSM: Acompanhamento Autônomo de Pacientes Explorando Ciência de Situação na IoT
Rogério da Costa Albandes, Adenauer Yamin, Jorge Luís Victória Barbosa et al. Anais de XXXV Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2019. Cites: paper

A Data-Driven Approach to Predicting Septic Shock in the Intensive Care Unit
Christopher R. Yee, Niven R. Narain, Viatcheslav R. Akmaev et al. Biomedical Informatics Insights, 2019. Cites: paper

Adversarial balancing-based representation learning for causal effect inference with observational data
Xin Du, Лэй Сун, Wouter Duivesteijn et al. TU/e Research Portal, 2019. Cites: paper

A Hybrid Normalization Method for Medical Concepts in Clinical Narrative using Semantic Matching.
Yen-Fu Luo, Weiyi Sun, Anna Rumshisky. PubMed Central, 2019. Cites: paper

A Multi-modal Deep Learning Method for Classifying Chest Radiology Exams
Nelson Nunes, Bruno Martins, Nuno André da Silva et al. Lecture notes in computer science, 2019. Cites: paper

An Analysis of Attention over Clinical Notes for Predictive Tasks
Sarthak Jain, Ramin Mohammadi, Byron Wallace. Clinical Natural Language Processing Workshop (ClinicalNLP), 2019. Cites: paper

A new model for tracking and detection of deterioration of vital signs based on artificial neural network
Tariq Ibrahim Al-Shwaheen, Wenhao Yuan. 2019. Cites: paper

An Interpretable Disease Onset Predictive Model Using Crossover Attention Mechanism From Electronic Health Records
Wei Guo, Wei Ge, Lizhen Cui et al. IEEE Access, 2019. Cites: paper

ARS_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System
Anumeha Agrawal, Rosa Anil George, Selvan Sunitha Ravi et al. BioNLP Workshop and Shared Task (BioNLP), 2019. Cites: paper

Artificial Intelligence in Critical Care
Piyush Mathur, Michael L Burns. International Anesthesiology Clinics, 2019. Cites: paper

Assessing the Readability of Freely Available ICU Notes.
Wu-Chen Su, Kevin R. Dufendach, Danny T Y Wu. PubMed Central, 2019. Cites: paper

A Supervised Approach for Patient-Specific ICU Mortality Prediction Using Feature Modeling
Gokul S Krishnan, S. Sowmya Kamath. Lecture notes in electrical engineering, 2019. Cites: paper

A survey of word embeddings for clinical text
Faiza Khan Khattak, Serena Jeblee, Chloé Pou-Prom et al. Journal of Biomedical Informatics, 2019. Cites: paper

Attention-Based Hierarchical Recurrent Neural Network for Phenotype Classification
Nan Xu, Yanyan Shen, Yanmin Zhu. Lecture notes in computer science, 2019. Cites: paper

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