COVID-19 Image Data Collection: Prospective Predictions Are the Future
- URL: http://arxiv.org/abs/2006.11988v3
- Date: Mon, 14 Dec 2020 18:52:43 GMT
- Title: COVID-19 Image Data Collection: Prospective Predictions Are the Future
- Authors: Joseph Paul Cohen and Paul Morrison and Lan Dao and Karsten Roth and
Tim Q Duong and Marzyeh Ghassemi
- Abstract summary: This dataset is the largest public resource for COVID-19 image and prognostic data.
It was manually aggregated from publication figures as well as various web based repositories into a machine learning friendly format.
We present multiple possible use cases for the data such as predicting the need for the ICU, predicting patient survival, and understanding a patient's trajectory during treatment.
- Score: 12.81240882490576
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to
streamline patient diagnosis and management has become more pressing than ever.
As one of the main imaging tools, chest X-rays (CXRs) are common, fast,
non-invasive, relatively cheap, and potentially bedside to monitor the
progression of the disease. This paper describes the first public COVID-19
image data collection as well as a preliminary exploration of possible use
cases for the data. This dataset currently contains hundreds of frontal view
X-rays and is the largest public resource for COVID-19 image and prognostic
data, making it a necessary resource to develop and evaluate tools to aid in
the treatment of COVID-19. It was manually aggregated from publication figures
as well as various web based repositories into a machine learning (ML) friendly
format with accompanying dataloader code. We collected frontal and lateral view
imagery and metadata such as the time since first symptoms, intensive care unit
(ICU) status, survival status, intubation status, or hospital location. We
present multiple possible use cases for the data such as predicting the need
for the ICU, predicting patient survival, and understanding a patient's
trajectory during treatment. Data can be accessed here:
https://github.com/ieee8023/covid-chestxray-dataset
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