# An Extensive Data Processing Pipeline for MIMIC-IV

arXiv: https://arxiv.org/abs/2204.13841 · HTML: https://mlsanity.com/paper/2204.13841/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 34 references that are in the map.
- First posted on arXiv 29 Apr 2022.

## Builds on (most cited first, 8 of 8)

- [Temporal Convolutional Networks for Action Segmentation and Detection](https://mlsanity.com/paper/1611.05267/) (2016)
- [Attention-Based Models for Speech Recognition](https://mlsanity.com/paper/1506.07503/) (2015)
- [Multitask learning and benchmarking with clinical time series data](https://mlsanity.com/paper/1703.07771/) (2017)
- [BEHRT: Transformer for Electronic Health Records](https://mlsanity.com/paper/1907.09538/) (2019)
- [MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III](https://mlsanity.com/paper/1907.08322/) (2019)
- [HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data](https://mlsanity.com/paper/2111.08536/) (2021)
- [Reproducibility in Machine Learning for Health](https://mlsanity.com/paper/1907.01463/) (2019)
- [Obesity Prediction with EHR Data: A deep learning approach with interpretable elements](https://mlsanity.com/paper/1912.02655/) (2019)

## Built on by (most cited first, 30 of 40)

- [EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models](https://mlsanity.com/paper/2307.02028/) (2023)
- [Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine](https://mlsanity.com/paper/2311.04937/) (2023)
- [Mimic-IV-ICD: A new benchmark for eXtreme MultiLabel Classification](https://mlsanity.com/paper/2304.13998/) (2023)
- [EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis](https://mlsanity.com/paper/2510.25628/) (2025)
- [Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage](https://mlsanity.com/paper/2403.03868/) (2024)
- [Unmasking the Chameleons: A Benchmark for Out-of-Distribution Detection in Medical Tabular Data](https://mlsanity.com/paper/2309.16220/) (2023)
- [Vertical Federated Learning with Missing Features During Training and Inference](https://mlsanity.com/paper/2410.22564/) (2024)
- [Benchmarking with MIMIC-IV, an irregular, spare clinical time series dataset](https://mlsanity.com/paper/2401.15290/) (2024)
- [Enforcing Fundamental Relations via Adversarial Attacks on Input Parameter Correlations](https://mlsanity.com/paper/2501.05588/) (2025)
- [Revisiting the MIMIC-IV Benchmark: Experiments Using Language Models for Electronic Health Records](https://mlsanity.com/paper/2504.20547/) (2025)
- [meds_reader: A fast and efficient EHR processing library](https://mlsanity.com/paper/2409.09095/) (2024)
- [Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction](https://mlsanity.com/paper/2507.06432/) (2025)
- [Cross-Representation Benchmarking in Time-Series Electronic Health Records for Clinical Outcome Prediction](https://mlsanity.com/paper/2510.09159/) (2025)
- [Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints](https://mlsanity.com/paper/2604.01841/) (2026)
- [HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks](https://mlsanity.com/paper/2403.18128/) (2024)
- [MENSA: A Multi-Event Network for Survival Analysis with Trajectory-based Likelihood Estimation](https://mlsanity.com/paper/2409.06525/) (2024)
- [A Multimodal Data Processing Pipeline for MIMIC-IV Dataset](https://mlsanity.com/paper/2601.11606/) (2026)
- [Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises](https://mlsanity.com/paper/2506.12808/) (2025)
- [SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis](https://mlsanity.com/paper/2511.11935/) (2025)
- [Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations](https://mlsanity.com/paper/2405.12658/) (2024)
- [Med-gte-hybrid: A contextual embedding transformer model for extracting actionable information from clinical texts](https://mlsanity.com/paper/2502.15996/) (2025)
- [Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health](https://mlsanity.com/paper/2502.16477/) (2025)
- [The CRITICAL Records Integrated Standardization Pipeline (CRISP): End-to-End Processing of Large-scale Multi-institutional OMOP CDM Data](https://mlsanity.com/paper/2509.08247/) (2025)
- [Towards symbolic regression for interpretable clinical decision scores](https://mlsanity.com/paper/2512.07961/) (2025)
- [A Multimodal Deep Learning Framework for Predicting ICU Deterioration: Integrating ECG Waveforms with Clinical Data and Clinician Benchmarking](https://mlsanity.com/paper/2601.06645/) (2026)
- [Challenges and recommendations for Electronic Health Records data extraction and preparation for dynamic prediction modelling in hospitalized patients -- a practical guide](https://mlsanity.com/paper/2501.10240/) (2025)
- [Towards Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospects](https://mlsanity.com/paper/2502.04899/) (2025)
- [Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes](https://mlsanity.com/paper/2503.06690/) (2025)
- [Validating Emergency Department Admission Predictions Based on Local Data Through MIMIC-IV](https://mlsanity.com/paper/2503.22706/) (2025)
- [Partial VOROS: A Cost-aware Performance Metric for Binary Classifiers with Precision and Capacity Constraints](https://mlsanity.com/paper/2510.18520/) (2025)

## Abstract (arXiv)

An increasing amount of research is being devoted to applying machine learning methods to electronic health record (EHR) data for various clinical purposes. This growing area of research has exposed the challenges of the accessibility of EHRs. MIMIC is a popular, public, and free EHR dataset in a raw format that has been used in numerous studies. The absence of standardized pre-processing steps can be, however, a significant barrier to the wider adoption of this rare resource. Additionally, this absence can reduce the reproducibility of the developed tools and limit the ability to compare the results among similar studies. In this work, we provide a greatly customizable pipeline to extract, clean, and pre-process the data available in the fourth version of the MIMIC dataset (MIMIC-IV). The pipeline also presents an end-to-end wizard-like package supporting predictive model creations and evaluations. The pipeline covers a range of clinical prediction tasks which can be broadly classified into four categories - readmission, length of stay, mortality, and phenotype prediction. The tool is publicly available at https://github.com/healthylaife/MIMIC-IV-Data-Pipeline.