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Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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inferredcites →https://doi.org/10.1038/s41746-021-00518-0openalex-snapshot
Imputation of missing values for electronic health record laboratory data
inferredcites →https://doi.org/10.1038/sdata.2016.35openalex-snapshot
MIMIC-III, a freely accessible critical care database
inferredcites →https://doi.org/10.1038/sdata.2018.178openalex-snapshot
The eICU Collaborative Research Database, a freely available multi-center database for critical care research
inferredcites →https://doi.org/10.1093/jamia/ocaa139openalex-snapshot
Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data
inferredcites →https://doi.org/10.1093/jamia/ocv189openalex-snapshot
SMART on FHIR: a standards-based, interoperable apps platform for electronic health records
inferredcites →https://doi.org/10.1093/jamia/ocx084openalex-snapshot
The MIMIC Code Repository: enabling reproducibility in critical care research
inferredcites →https://doi.org/10.1093/labmed/lmaa111openalex-snapshot
Machine Learning Prediction of SARS-CoV-2 Polymerase Chain Reaction Results with Routine Blood Tests
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Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis
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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*
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Machine Learning and Decision Support in Critical Care
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Change Point Detection in Time Series Data Using Autoencoders With a Time-Invariant Representation
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Heat Shock Protein A12B Protects Vascular Endothelial Cells Against Sepsis-Induced Acute Lung Injury in Mice
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A basic model for assessing primary health care electronic medical record data quality
inferredcites →https://doi.org/10.1186/s12911-021-01630-7openalex-snapshot
An automated data cleaning method for Electronic Health Records by incorporating clinical knowledge
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Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study
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TabNet: Attentive Interpretable Tabular Learning
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inferredcites →https://doi.org/10.2196/13043openalex-snapshot
Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform
inferredcites →https://doi.org/10.25080/majora-92bf1922-00aopenalex-snapshot
Data Structures for Statistical Computing in Python
inferredcites →https://doi.org/10.3390/healthcare10010085openalex-snapshot
Empirical Study on Classifiers for Earlier Prediction of COVID-19 Infection Cure and Death Rate in the Indian States
inferredcites →https://doi.org/10.3390/jpm11090893openalex-snapshot
COVID Mortality Prediction with Machine Learning Methods: A Systematic Review and Critical Appraisal
inferredcites →https://doi.org/10.4338/aci-2017-03-cr-0046openalex-snapshot
Barriers to Achieving Economies of Scale in Analysis of EHR Data
inferredcites →https://doi.org/10.5334/egems.218openalex-snapshot
A Data Quality Assessment Guideline for Electronic Health Record Data Reuse
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Medifusionvec: A Knowledge Representation Learning Model for Semantic Representation of Medical Information Hierarchical Models
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inferred← citeshttps://doi.org/10.2196/52508openalex-snapshot
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)
inferred← citeshttps://doi.org/10.2196/73987openalex-snapshot
Challenges and Recommendations for Electronic Health Records Data Extraction and Preparation for Dynamic Prediction Modeling in Hospitalized Patients: Practical Guide and Tutorial
inferred← citeshttps://doi.org/10.2196/preprints.52508openalex-snapshot
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS) (Preprint)
inferred← citeshttps://doi.org/10.3389/fdgth.2026.1747227openalex-snapshot
Extraction and processing of intensive care chart data from a patient data management system
inferred← citeshttps://doi.org/10.3389/fdgth.2026.1769337openalex-snapshot
Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review
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Classical Association Rule Mining Algorithms for Medical Data Analysis
inferred← citeshttps://doi.org/10.55813/gaea/rcym/v4/n1/126openalex-snapshot
Modelo de Inteligencia artificial para el diagnóstico del dengue
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Understanding pain in women with polyendocrine metabolic ovarian syndrome: health risks and treatment effectiveness
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Understanding Pain in Polycystic Ovary Syndrome: Health Risks and Treatment Effectiveness
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lab: an R package for generating analysis-ready data from laboratory records
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