Resources

Deep learning technologies have been widely adopted in medical imaging due to their ability to extract features from images and make accurate diagnoses automatically. Medical imaging technologies are particularly useful because they can be trained t…

A respiratory pressure, flow, and dynamic circumference (chest and abdominal) dataset was collected from 30 healthy adults at the University of Canterbury under Human Research Ethics Committee (HREC) ethics. Pressure and flow data was collected usin…

The advent of large, open access text databases has driven advances in state-of-the-art model performance in natural language processing (NLP). The relatively limited amount of clinical data available for NLP has been cited as a significant barrier …

We present a radiology question answering dataset, RadQA, with 3074 questions posed against radiology reports and annotated with their corresponding answer spans (resulting in a total of 6148 question-answer evidence pairs) by physicians. The questi…

Reliable longitudinal risk prediction for hospitalized patients is needed to provide quality care. Our goal is to foster the development of generalizable models capable of leveraging clinical notes to predict healthcare-associated diseases 24–96 hou…

This dataset includes multimodal physiologic, flight performance, and user interaction data streams, collected as participants performed virtual flight tasks of varying difficulty. In virtual reality, individuals flew an "Instrument Landing System" …

The Brazilian labeled chest x-ray dataset (BRAX) is an automatically labeled dataset designed to assist researchers in the validation of machine learning models. The dataset contains 24,959 chest radiography studies from patients presenting to a lar…

Continuous monitoring of arterial blood pressure (BP) in non-clinical (ambulatory) settings is essential for a proper understanding of numerous health conditions. While conventional ambulatory BP devices exist, they are uncomfortable, bulky, and in…

Electronic Health Records (EHR) contain patient records, stored in structured tables as well as unstructured clinical notes. The information in structured and unstructured EHR records is not strictly disjoint: information may be duplicated, contradi…

There is a shortage of text medical resources for the Russian language. This is a substantial obstacle in state-of-the-art NLP deep learning models research and development. To mitigate this issue we translated the MedNLI data from English to Russia…