Participants of the challenge will be tasked with developing machine-learning algorithms capable of detecting pneumothorax on chest x-rays as well as prioritizing patients for expedited review. Ahead of the competition, radiologists from SIIM and STR have used MD.ai's web-based tool to annotate the radiographs and have stored the dataset in Kaggle's cloud-based data platform.
"This Kaggle competition will result in open-source algorithms to help solve a serious healthcare problem that can lead to death if not identified and treated quickly," Dr. Bibb Allen Jr., chief medical officer of the ACR Data Science Institute, said in a statement.
The societies will launch the challenge June 26 to 28 at the 2019 SIIM meeting in Aurora, CO. They will deliver awards to the winning teams during the 2019 SIIM Conference on Machine Intelligence in Medical Imaging (C-MIMI) taking place September 22 to 23 in Austin, TX.
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