Resources


Database Open Access

Apnea-ECG Database

The data consist of 70 records, divided into a learning set of 35 records (a01 through a20, b01 through b05, and c01 through c10), and a test set of 35 records (x01 through x35), all of which may be downloaded from this page. Recordings vary in leng…

ecg sleep apnea challenge multiparameter

Published: Feb. 10, 2000. Version: 1.0.0

Visualize waveforms

Database Credentialed Access

Paediatric Intensive Care database

Haomin Li, Xian Zeng, Gang Yu

PIC (Paediatric Intensive Care) is a large paediatric-specific, single-centre, bilingual database comprising information relating to children admitted to critical care units at a large children’s hospital in China.

critical care intensive care natural language processing pediatrics

Published: Dec. 1, 2019. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR-JPG - chest radiographs with structured labels

Alistair Johnson, matt lungren, Yifan Peng, Zhiyong Lu, Roger Mark, Seth Berkowitz, Steven Horng

Chest x-rays in JPG format with structured labels derived from the associated radiology report.

mimic computer vision radiology deep learning chest x-ray

Published: Nov. 14, 2019. Version: 2.0.0

Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, Seth Berkowitz, Steven Horng

Chest radiographs in DICOM format with associated free-text reports.

mimic machine learning natural language processing chest x-rays computer vision radiology

Published: Sept. 19, 2019. Version: 2.0.0

Database Credentialed Access

MIMIC-III Clinical Database

Alistair Johnson, Tom Pollard, Roger Mark

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012.

The databa…

critical care intensive care machine learning natural language processing clinical

Published: Sept. 4, 2016. Version: 1.4

Database Credentialed Access

MedNLI - A Natural Language Inference Dataset For The Clinical Domain

Chaitanya Shivade

This is a resource for training machine learning models for language inference in the medical domain.

recognizing textual entailment natural language inference

Published: Oct. 1, 2019. Version: 1.0.0

Software Open Access

Random Search Toolbox

A major issue with many signal processing and machine learning algorithms is the lack of optimisation methods for determining the numerous hyper-parameters associated with the model as well as the knowledge of which hyper-parameters are relevant. Th…

Published: Nov. 4, 2014. Version: 1.0.0