Introducing the BlendedICU dataset, the first harmonized, international intensive care dataset

[1]  Alistair E. W. Johnson,et al.  MIMIC-IV, a freely accessible electronic health record dataset , 2023, Scientific Data.

[2]  Tao Huang,et al.  Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units , 2022, Heart & lung : the journal of critical care.

[3]  Rahmatollah Beheshti,et al.  An Extensive Data Processing Pipeline for MIMIC-IV , 2022, ML4H@NeurIPS.

[4]  R. Zwiggelaar,et al.  A systematic review of the prediction of hospital length of stay: Towards a unified framework , 2022, PLOS digital health.

[5]  L. Celi,et al.  Systematic Review and Comparison of Publicly Available ICU Data Sets—A Decision Guide for Clinicians and Data Scientists , 2022, Critical care medicine.

[6]  Gunnar Rätsch,et al.  HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data , 2021, NeurIPS Datasets and Benchmarks.

[7]  Antoine Lamer,et al.  Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study , 2021, JMIR medical informatics.

[8]  Xiaoli Liu,et al.  Development and validation of a model for the early prediction of the RRT requirement in patients with rhabdomyolysis. , 2021, The American journal of emergency medicine.

[9]  G. Clermont,et al.  Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example* , 2021, Critical care medicine.

[10]  Chava L. Ramspek,et al.  External validation of prognostic models: what, why, how, when and where? , 2020, Clinical kidney journal.

[11]  Danai Koutra,et al.  Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data , 2020, J. Am. Medical Informatics Assoc..

[12]  Stephanie L. Hyland,et al.  Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit , 2020, CHIL.

[13]  Karsten M. Borgwardt,et al.  Early prediction of circulatory failure in the intensive care unit using machine learning , 2020, Nature Medicine.

[14]  V. Osmani,et al.  Benchmarking machine learning models on multi-centre eICU critical care dataset , 2019, PloS one.

[15]  Alistair E. W. Johnson,et al.  The eICU Collaborative Research Database, a freely available multi-center database for critical care research , 2018, Scientific Data.

[16]  OUP accepted manuscript , 2021, Brain.

[17]  G. Xie,et al.  A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation , 2020, AMIA.

[18]  Yu-Chuan Li,et al.  Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers , 2015, MedInfo.

[19]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .