ArticleJournal of the American Medical Informatics Association : JAMIA2018
The MIMIC Code Repository: enabling reproducibility in critical care research.
Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers.
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Who cites it
215 citing papers in PubMed.
- medicalcoder: a unified and longitudinally aware framework for International Classification of Diseases code-based comorbidity assessment in R.JAMIA open · 2026Article
- Lymphopenia and elevated NLR identify patients with septic shock who may benefit from corticosteroids: a target trial emulation study.Intensive care medicine experimental · 2026Article
- Navigating Healthcare AI Governance: the Comprehensive Algorithmic Oversight and Stewardship Framework for Risk and Equity.Health care analysis : HCA : journal of health philosophy and policy · 2026Article
- Associations between pneumonia with sepsis, sepsis-associated encephalopathy, and mortality in adult intensive care unit: a retrospective analysis using MIMIC-IV database.Journal of thoracic disease · 2026Article
- Comorbidity phenotypes and the incidence and severity of acute kidney injury in older critically ill patients: a retrospective cohort study.BMC geriatrics · 2026Article
- MAP: evaluation and multi-agent enhancement of large language models for inpatient pathways.npj health systems · 2026Article
- Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study.Intensive care medicine experimental · 2026Article
- Lactate dehydrogenase-to-Albumin Ratio (LAR) predicts mortality in critically ill patients with hypertensive heart failure: A MIMIC-IV database analysis.Clinics (Sao Paulo, Brazil) · 2026Article
- Illness severity modifies the association between sepsis and survival in critically ill patients with acute kidney injury.Clinical and experimental nephrology · 2026Article
- Association between acute kidney injury and delirium in critically ill patients: a retrospective cohort study using two independent databases.Critical care (London, England) · 2026Article
- Glycemic Variability as a Predictor of Mortality in Sepsis Patients With Concurrent Persistent Inflammation, Immunosuppression, and Catabolism Syndrome.Immunity, inflammation and disease · 2026Article
- Continuous Evaluation Frameworks for Retrospective Evaluation of Clinical Machine Learning Models.Critical care (London, England) · 2026Article
- Unbiased clustering of acute-on-chronic liver failure patients using machine learning in a real-world ICU cohort.Nature communications · 2026Article
- ICU mortality prediction via multimodal learning on MIMIC-IV clinical data.Bioinformatics advances · 2026Article
- Prognostic discrimination of SOFA-2 vs. SOFA-1 and incremental information from cardiovascular scoring and vasoactive support intensity in patients with sepsis receiving early vasoactive therapy.Frontiers in cardiovascular medicine · 2026Article
- Early prediction of vasopressor initiation in ICU sepsis patients using an interpretable EHR-based ML model.BMC medical informatics and decision making · 2025Article
- Development and validation of an interpretable predictive machine learning model for successful weaning of continuous renal replacement therapy.Scientific reports · 2025Observational
- Charlson index predicts thirtyday mortality in critically ill stroke patients MIMICIV retrospective study.Scientific reports · 2025Article
- Article
- Association between the systemic immune-inflammation index and mortality risk in myocardial infarction patients: a retrospective cohort study.European journal of medical research · 2025Article
155 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
Objective: Lack of reproducibility in medical studies is a barrier to the generation of a robust knowledge base to support clinical decision-making. In this paper we outline the Medical Information Mart for Intensive Care (MIMIC) Code Repository, a centralized code base for generating reproducible studies on an openly available critical care dataset. Materials and Methods: Code is provided to load the data into a relational structure, create extractions of the data, and reproduce entire analysis plans including research studies. Results: Concepts extracted include severity of illness scores, comorbid status, administrative definitions of sepsis, physiologic criteria for sepsis, organ failure scores, treatment administration, and more. Executable documents are used for tutorials and reproduce published studies end-to-end, providing a template for future researchers to replicate. The repository's issue tracker enables community discussion about the data and concepts, allowing users to collaboratively improve the resource. Discussion: The centralized repository provides a platform for users of the data to interact directly with the data generators, facilitating greater understanding of the data. It also provides a location for the community to collaborate on necessary concepts for research progress and share them with a larger audience. Consistent application of the same code for underlying concepts is a key step in ensuring that research studies on the MIMIC database are comparable and reproducible. Conclusion: By providing open source code alongside the freely accessible MIMIC-III database, we enable end-to-end reproducible analysis of electronic health records.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.