Publications citing MIMIC-III Waveform Database v1.0

Concept-based model explanations for electronic health records
Diana Mincu, Eric Loreaux, Shaobo Hou et al. ACM Conference on Health, Inference, and Learning (CHIL), 2021. Cites: paper

Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study
Rahuldeb Sarkar, Christopher Martin, Heather Mattie et al. The Lancet Digital Health, 2021. Cites: paper

Phenotypical ontology driven framework for multi-task learning
Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraporty et al. ACM Conference on Health, Inference, and Learning (CHIL), 2021. Cites: paper

Predictive models for colorectal cancer recurrence using multi-modal healthcare data
Danliang Ho, Iain Bee Huat Tan, Mehul Motani. ACM Conference on Health, Inference, and Learning (CHIL), 2021. Cites: paper

Survival in the Intensive Care Unit: A prognosis model based on Bayesian classifiers
Rosario Delgado, J. David Núñez-González, Juan Carlos Yébenes et al. Artificial Intelligence in Medicine, 2021. Cites: paper

Variable selection for causal mediation analysis using LASSO-based methods
Zhaoxin Ye, Yeying Zhu, Donna L. Coffman. Statistical Methods in Medical Research, 2021. Cites: paper

Early prediction of cause-specific acute respiratory distress syndrome via interpretable machine-learning.
Junwei Wu, Chao Liu, Lixin Xie et al. Research Square, 2021. Cites: paper

Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU
Oisín Fitzgerald, Oscar Perez‐Concha, Blanca Gallego et al. Journal of the American Medical Informatics Association, 2021. Cites: paper

BERTSurv: BERT-Based Survival Models for Predicting Outcomes of Trauma Patients
Yun Zhao, Qinghang Hong, Xinlu Zhang et al. arXiv (Cornell University), 2021. Cites: paper

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism
Nicolas A. Aguirre, Edith Grall‐Maës, Leandro J. Cymberknop et al. Sensors, 2021. Cites: paper

EMR2vec: Bridging the gap between patient data and clinical trial
Houssein Dhayne, Rima Kilany, Rafiqul Haque et al. Computers & Industrial Engineering, 2021. Cites: paper

Platelet Transfusion is Not Associated with the Better Outcomes of Patients with Sepsis-Induced Thrombocytopenia: A Propensity Score-Matching Analysis.
Aiming Zhou, Shanshan Wu, Qin Chen et al. Research Square, 2021. Cites: paper

Data Mining in Healthcare: Applying Strategic Intelligence Techniques to Depict 25 Years of Research Development
Maikel Luis Kolling, Leonardo B. Furstenau, Michele Kremer Sott et al. International Journal of Environmental Research and Public Health, 2021. Cites: paper

A Preliminary Characterization of Canonicalized and Non-Canonicalized Section Headers Across Variable Clinical Note Types
Junjie Wang, Shun Yu, Anahita Davoudi et al. medRxiv, 2021. Cites: paper

Classification évidentielle mono- et multi-label : application à la détection de maladies cardio-vasculaires
Mohamed Mroueh Dit Injibar. 2021. Cites: paper

Use of learning approaches to predict clinical deterioration in patients based on various variables: a review of the literature
Tariq Ibrahim Al-Shwaheen, Mehrdad Moghbel, Yuan Wen Hau et al. Artificial Intelligence Review, 2021. Cites: paper

A Data-driven Framework for Learning and Visualizing Characteristics of Thrombotic Event Phenotypes from Clinical Texts
Anahita Davoudi, Audrey Yang, Sy Hwang et al. medRxiv, 2021. Cites: paper

Development and Validation of a 90-day Mortality Prediction Nomogram for AMI Patients: A Retrospective Cohort Study
Rui Yang, Wen Ma, Tao Huang et al. Research Square, 2021. Cites: paper

Doubly robust confidence sequences for sequential causal inference
Ian Waudby-Smith, David T. Arbour, Ritwik Sinha et al. arXiv (Cornell University), 2021. Cites: paper

Automated Coding of Under-Studied Medical Concept Domains: Linking Physical Activity Reports to the International Classification of Functioning, Disability, and Health
Denis Newman-Griffis, Eric Fosler-Lussier. Frontiers in Digital Health, 2021. Cites: paper

Data-driven curation process for describing the blood glucose management in the intensive care unit
Aldo Robles Arévalo, Jason H. Maley, Lawrence Baker et al. Scientific Data, 2021. Cites: paper

Improving biomedical word representation with locally linear embedding
Di Zhao, Jian Wang, Yonghe Chu et al. Neurocomputing, 2021. Cites: paper

Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance
Joshua R. Minot, Nicholas Cheney, Marc E. Maier et al. arXiv (Cornell University), 2021. Cites: paper

A novel model to label delirium in an intensive care unit from clinician actions
Caitlin E. Coombes, Kevin R. Coombes, Naleef Fareed. BMC Medical Informatics and Decision Making, 2021. Cites: paper

A promising predictor of mortality— A cohort study (Preprint)
Ji Ha Ling. 2021. Cites: paper

Challenges for Reinforcement Learning in Healthcare
Elsa Riachi, Muhammad Mamdani, Michael Fralick et al. arXiv (Cornell University), 2021. Cites: paper

Development and validation of a nomogram to predict the mortality risk in elderly patients with ARF
Junnan Xu, Jie Weng, Jingwen Yang et al. PeerJ, 2021. Cites: paper

Explainable automated coding of clinical notes using hierarchical label-wise attention networks and label embedding initialisation
Hang Dong, Víctor Suárez-Paniagua, William N. Whiteley et al. Journal of Biomedical Informatics, 2021. Cites: paper

Extracting clinical terms from radiology reports with deep learning
Kento Sugimoto, Toshihiro Takeda, Jong–Hoon Oh et al. Journal of Biomedical Informatics, 2021. Cites: paper

Generalized and transferable patient language representation for phenotyping with limited data
Yuqi Si, Elmer Victor Bernstam, Kirk E Roberts. Journal of Biomedical Informatics, 2021. Cites: paper

Hacking the hackathon: insights from hosting a novel trainee-oriented multidisciplinary event
Maelys J. Amat, Erin R. Duralde, Barbara D. Lam et al. BMJ Innovations, 2021. Cites: paper

Outcomes prediction in longitudinal data: Study designs evaluation, use case in ICU acquired sepsis
Maya Schvetz, Lior Fuchs, Victor Novack et al. Journal of Biomedical Informatics, 2021. Cites: paper

Towards graph-based class-imbalance learning for hospital readmission
Guodong Du, Jia Zhang, Fenglong Ma et al. Expert Systems with Applications, 2021. Cites: paper

Development and validation of a model for the early prediction of the RRT requirement in patients with rhabdomyolysis
Chao Liu, Qian Yuan, Zhi Mao et al. The American Journal of Emergency Medicine, 2021. Cites: paper

In-hospital Mortality Prediction among Patients with Fractures of Pelvis and Acetabulum in Intensive Care Unit: Machine Learning versus Conventional System
Yanrong Cai, Xiang Jiang, Weifan Dai et al. Research Square, 2021. Cites: paper

Using nursing notes to improve clinical outcome prediction in intensive care patients: A retrospective cohort study
Kexin Huang, Tamryn Fowler Gray, Santiago Romero Brufau et al. Journal of the American Medical Informatics Association, 2021. Cites: paper

An Estimation Method of Continuous Non-Invasive Arterial Blood Pressure Waveform Using Photoplethysmography: A U-Net Architecture-Based Approach
Tasbiraha Athaya, Sunwoong Choi. Sensors, 2021. Cites: paper

An explainable machine learning algorithm for risk factor analysis of in-hospital mortality in sepsis survivors with ICU readmission
Zhengyu Jiang, Lulong Bo, Zhenhua Xu et al. Computer Methods and Programs in Biomedicine, 2021. Cites: paper

Learning to Treat Hypotensive Episodes in Sepsis Patients Using a Counterfactual Reasoning Framework
Russell Jeter, Li-wei H. Lehman, Christopher S. Josef et al. medRxiv, 2021. Cites: paper

Nomogram to predict the risk of acute kidney injury in patients with diabetic ketoacidosis: an analysis of the MIMIC-III database
Tingting Fan, Haosheng Wang, Jiaxin Wang et al. BMC Endocrine Disorders, 2021. Cites: paper

Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series
Ahmad Wisnu Mulyadi, Eunji Jun, Heung‐Il Suk. IEEE Transactions on Cybernetics, 2021. Cites: paper

Using Gated Recurrent Units Models for Early Prediction of Sepsis in The Intensive Care Unit
Xuze Zhao, Bo Qu. Research Square, 2021. Cites: paper

Application of Machine Learning in Intensive Care Unit (ICU) Settings Using MIMIC Dataset: Systematic Review
Mahanazuddin Syed, Shorabuddin Syed, Kevin Wayne Sexton et al. Informatics, 2021. Cites: paper

A Prediction Model for Assessing Prognosis in Critically Ill Patients with Sepsis-associated Acute Kidney Injury
Hongbin Hu, Lulan Li, Yuan Zhang et al. Shock, 2021. Cites: paper

A review of irregular time series data handling with gated recurrent neural networks
Philip B. Weerakody, Kok Wai Wong, Guanjin Wang et al. Neurocomputing, 2021. Cites: paper

Contextual Embeddings from Clinical Notes Improves Prediction of Sepsis
Fatemeh Amrollahi, Supreeth Prajwal Shashikumar, Fereshteh Razmi et al. medRxiv, 2021. Cites: paper

Technical Report on Data Integration and Preparation
El Kindi Rezig, Michael Cafarella, Vijay N. Gadepally. arXiv (Cornell University), 2021. Cites: paper

The rebound of platelet count could be a predictor of good prognosis of sepsis in the intensive care unit: a retrospective analysis of the large clinical database MIMIC-III
Huang Fa, Jinghong Xu, Tong Li et al. Research Square, 2021. Cites: paper

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit
Xihua Huang, Zhenyu Liang, Tang Li et al. International Health, 2021. Cites: paper

Automated coding of under-studied medical concept domains: linking physical activity reports to the international classification of functioning, disability, and health
Newman-Griffis, D., Fosler-Lussier, E. White Rose Research Online (University of Leeds, The University of Sheffield, University of York), 2021. Cites: paper

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