Resources

A pressure and flow dataset for CPAP (continuous positive airway pressure) breathing obtained from 30 subjects for model-based identification of patient-specific lung mechanics using a specially designed sensor system comprising an array of differen…

Computer-aided diagnosis systems in adult chest radiography (CXR) have recently achieved great success thanks to the availability of large-scale, annotated datasets and the advent of high-performance supervised learning algorithms. However, the deve…

This dataset of electrodermal activity was collected from 11 healthy volunteer subjects who were awake and at rest in seated position. The activity was recorded from each subject's non-dominant hand for one hour at 256 Hz. Electrodermal activity mea…

This dataset of electrodermal activity was collected from 11 healthy volunteer subjects who were awake and at rest in seated position and 11 different healthy volunteers who were under controlled propofol sedation. For the awake and at rest subjects…

The problem of natural language inference (NLI) determines whether a natural language hypothesis can be justifiably inferred from a natural language premise. NLI has attracted researchers to benchmark it in a number of settings including medical one…

This is a preprocessed dataset derived from patient records in MIMIC-III and eICU, two large-scale electronic health record (EHR) databases. It contains features and labels for 5 prediction tasks involving 3 adverse outcomes (prediction times listed…

The Gout Emergency Department Chief Complaint Corpora (GED3C) consists of 2 corpora of free text triage nurse chief complaints (up to 282 characters in length) collected from 2019 to 2020 at an academic medical center in the Deep South. The smaller …

Natural Language Inference (NLI) is the task of determining whether a given hypothesis can be inferred from a given premise. Also known as Recognizing Textual Entailment (RTE), this task has enjoyed popularity among researchers for some time. Howeve…

State of the art models using deep neural networks have become very good in learning an accurate mapping from inputs to outputs. However, they still lack generalization capabilities in conditions that differ from the ones encountered during training…

Unlocking the full potential of clinical notes within electronic health records presents a challenge for large scale, computational analyses. Many studies that incorporate information from clinical notes do so with simple word-matching approaches an…