RSNA Pneumonia Detection Machine Learning Challenge Now Open
Submissions due Oct. 24 and winners to be recognized at RSNA 2018.
August 27, 2018
Registration is open for the RSNA Pneumonia Detection Machine Learning (ML) Challenge. This year’s challenge invites teams to develop algorithms to identify and localize pneumonia in chest x-rays.
The Pneumonia Detection Challenge will be based on a publicly available dataset published by the National Institutes of Health that has been carefully annotated by multiple expert reviewers. The RSNA Machine Learning Steering Subcommittee collaborated with volunteer specialists from the Society of Thoracic Radiology to annotate the dataset, identifying abnormal areas in the lung images and assessing the probability of pneumonia.
This year’s challenge will be conducted using the competition platform provided by Kaggle, Inc. (a subsidiary of Alphabet, Inc., which is also the parent company of Google). The Kaggle platform will provide a home page for the challenge, controlled access to the challenge datasets, a discussion forum for participants and the repository where they submit their results. Kaggle has recognized the RSNA Pneumonia Detection Challenge as a public good and will provide $30,000 in prize money for the winning entries.
The training phase is open and runs until Oct. 17. The evaluation phase runs Oct. 18-24. The deadline for submission of test results is Oct. 24. Submissions will be compared to the “ground-truth” values supplied by the annotations of the expert observers to determine the winners.
The results will be announced in early November and the top submissions will be recognized Nov. 26 in a session at the Machine Learning Showcase during RSNA 2018.
Radiologists interested in participating can set up a free account on the Kaggle site and express their interests and qualifications in the forum for the RSNA Pneumonia Detection Challenge.
Questions about the RSNA Pneumonia Detection ML Challenge should be directed to informatics@rsna.org.
The Pneumonia Detection Challenge will be based on a publicly available dataset published by the National Institutes of Health that has been carefully annotated by multiple expert reviewers. The RSNA Machine Learning Steering Subcommittee collaborated with volunteer specialists from the Society of Thoracic Radiology to annotate the dataset, identifying abnormal areas in the lung images and assessing the probability of pneumonia.
This year’s challenge will be conducted using the competition platform provided by Kaggle, Inc. (a subsidiary of Alphabet, Inc., which is also the parent company of Google). The Kaggle platform will provide a home page for the challenge, controlled access to the challenge datasets, a discussion forum for participants and the repository where they submit their results. Kaggle has recognized the RSNA Pneumonia Detection Challenge as a public good and will provide $30,000 in prize money for the winning entries.
The training phase is open and runs until Oct. 17. The evaluation phase runs Oct. 18-24. The deadline for submission of test results is Oct. 24. Submissions will be compared to the “ground-truth” values supplied by the annotations of the expert observers to determine the winners.
The results will be announced in early November and the top submissions will be recognized Nov. 26 in a session at the Machine Learning Showcase during RSNA 2018.
Radiologists interested in participating can set up a free account on the Kaggle site and express their interests and qualifications in the forum for the RSNA Pneumonia Detection Challenge.
Questions about the RSNA Pneumonia Detection ML Challenge should be directed to informatics@rsna.org.
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