Help accelerate Alzheimer's research by automatically classifying which blood vessels are flowing and which are stalled.
We see tremendous opportunity to incorporate these models into Stall Catchers, where they could work in concert with human-based analysis to double or triple our analytic throughput without compromising data quality. This could get us closer to an Alzheimer’s treatment at unprecedented analytic speeds.
— Pietro Michelucci, Project Lead, Stall Catchers
5.8 million Americans live with Alzheimer’s dementia, including 10% of all seniors 65 and older. Scientists at Cornell have discovered links between “stalls,” or clogged blood vessels in the brain, and Alzheimer’s. The ability to prevent or remove stalls may transform how Alzheimer’s disease is treated. However, finding these stalls is extremely time intensive, especially as only around 1% of image stacks contain stalls.
In this challenge, participants were tasked with building machine learning models that could classify blood vessels in 3D image stacks as stalled or flowing. The exceptional challenge dataset came from Stall Catchers, a citizen science project that crowdsources the identification of stalls using research data provided by Cornell University’s Department of Biomedical Engineering.
The researchers behind Stall Catchers believe that some portion of the data may be within reach of machine learning models. Model predictions would only be used in cases where models had been validated to meet the researchers’ data quality requirements.
The top-performing model was able to achieve an impressive 0.855 Matthew's correlation coefficient (MCC) score, surpassing 85% sensitivity (true positive rate, i.e. classifying stalled vessels as such) and 99% specificity (true negative rate, i.e. classifying flowing vessels as such). This level of specificity means that models like this can be used to process large volumes of data while minimizing the risk of losing the stalled cases that are so important to research.
The greatest immediate promise from these results lies in combining machine and human predictions to accelerate research, by 1) using algorithms and humans in tandem to process data far more quickly, and 2) continuing experimentation to develop methods that combine algorithms and humans in ways that exceed the performance that either demonstrates alone. All prize-winning solutions from this competition are linked below and made available for anyone to use and learn from.
Clog Loss: Advance Alzheimer’s Research with Stall Catchers: Rules and Terms of Data Use
DrivenData Competition Rules
One account per participant
You cannot sign up to DrivenData from multiple accounts and therefore you cannot submit from multiple accounts.
Private sharing of code
Privately sharing code or data outside of teams is not permitted.
Public dissemination of entries
DrivenData has the right to publicly disseminate any entries or models.
Qualified open licensing of winners
Winning solutions need to be made available under The MIT License (an open source software license commonly described at http://opensource.org/licenses/MIT), with the exception of uses of Sponsor-provided software as described on the Competition Website, in order to be eligible for recognition and prize money if offered.
Documentation for winning solutions
Winning solutions must be documented using the provided Winning Model Documentation Template in order to be eligible for recognition and prize money if offered.
The number of submissions per day is restricted to a fixed value on a per-competition basis. Any attempt to circumvent this limit will result in disqualification.
External data is not allowed unless otherwise noted explicitly on these competition pages. Participants agree to make no attempt to use additional data or data sources not provided on these competition pages.
These are the complete, official rules for the Competition (the "Competition Rules") and incorporate by reference the contents of the Competition Website listed above.
By downloading a dataset linked from the Competition Website, submitting an entry to this Competition, or joining a Team in this Competition, you are agreeing to be bound by these Competition Rules which constitute a binding agreement between you and DrivenData and, if applicable, any rules and restrictions that may be imposed by the Competition Sponsor.
The Competition is hosted by DrivenData, Inc ("DrivenData"). The Competition will run according to the dates listed on the Competition Website (the "Competition Period").
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USER SUBMISSIONS MUST IN THEIR ENTIRETY COMPLY WITH ALL APPLICABLE FEDERAL, STATE, LOCAL, AND INTERNATIONAL LAWS AND REGULATIONS. WITHOUT LIMITING THE FOREGOING, IN ORDER TO BE ELIGIBLE, YOU WARRANT THAT (UNLESS OTHERWISE SPECIFIED IN THE PROBLEM STATEMENT) YOUR SUBMISSION FOR THIS COMPETITION:
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- Has not been entered in previous challenges, or won previous awards.
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- Is suitable for a general audience.
- Does not contain any claims that are not and cannot be substantiated or that would be false and/or misleading to a reasonable consumer.
Selection of winners
This Competition is a challenge of skill and the final results are determined by evaluating a combination of quantitative and qualitative factors, as more fully described on the Competition Website. For that portion of the Competition evaluated quantitatively, the results will be determined solely by leaderboard ranking on the private leaderboard based on an objective statistical evaluation metric published on the Competition Website prior to commencement of the Competition (subject to compliance with these Competition Rules). Participants' scores and ranks on the Competition Website at any given stage of the Competition will be based on the objective statistical evaluation metric described on the Competition Website, as determined by applying the predictions in the Submission to the ground truth of a validation dataset whose instances were a fixed set sampled from the Data. For that portion of the Competition evaluated qualitatively, the results will be determined by a panel of judges, as more fully described on the Competition Website. As more fully described on the Competition Website, the Competition may have a quantitative winner, a qualitative winner, a combined quantitative and qualitative winner, or all three.
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- disqualify your Submission(s); or
- require that you remediate within one week all issues identified in your Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).
A tie between two or more valid and identically ranked submissions will be resolved in favor of the tied submission that was submitted first.
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Prizes and conditions
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As a condition of receipt of the prize, winner must deliver the algorithm's code and documentation to DrivenData. The source code must contain a description of resources required to build and run the algorithm. The accompanying documentation should be consistent with DrivenData's Winning Model Documentation Template, which will be provided to winners within 30 days of the end of the Competition Period.
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- represents that he/she/it has the unrestricted right to grant that license.
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DrivenData reserves the right to request information associated with our investigation of suspected cheating. Failure to respond to these requests (including failure to furnish the requested information) within ten (10) days is grounds for disqualification.
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Data use and code sharing
DATA. "Data" means the Data or Datasets linked from the Competition Website for the purpose of use by Participants in the Competition. For the avoidance of doubt, Data is deemed for the purpose of these Competition Rules to include any prototype or executable code provided to Participants by DrivenData or via the Competition Website. Participants must use the Data only as permitted by these Competition Rules and any associated data use rules specified on the Competition Website.
Unless otherwise permitted by the terms of the Competition Website, Participants must use the Data solely for the purpose and duration of the Competition, including but not limited to reading and learning from the Data, analyzing the Data, modifying the Data and generally preparing your Submission and any underlying models and participating in forum discussions on the Competition Website. Participants agree to use suitable measures to prevent persons who have not formally agreed to these Competition Rules from gaining access to the Data and agree not to transmit, duplicate, publish, redistribute or otherwise provide or make available the Data to any party not participating in the Competition. Participants agree to notify DrivenData immediately upon learning of any possible unauthorized transmission or unauthorized access of the Data and agree to work with DrivenData to rectify any unauthorized transmission. Participants agree that participation in the Competition shall not be construed as having or being granted a license (expressly, by implication, estoppel, or otherwise) under, or any right of ownership in, any of the Data.
EXTERNAL DATA. Unless otherwise expressly stated on the Competition Website, Participants must not use data other than the Data to develop and test their models and Submissions. Competition Sponsor reserves the right in its sole discretion to disqualify any Participant who Competition Sponsor discovers has undertaken or attempted to undertake the use of data other than the Data, or who uses the Data other than as permitted according to the Competition Website and in these Competition Rules, in the course of the Competition.
CODE SHARING. Participants are prohibited from privately sharing source or executable code developed in connection with or based upon the Data, and any such sharing is a breach of these Competition Rules and may result in disqualification. Participants are permitted to publicly share source or executable code developed in connection with or based upon the Data, or otherwise relevant to the Competition, provided that such sharing does not violate the intellectual property rights of any third party. By so sharing, the sharing Participant is thereby deemed to have licensed the shared code under the MIT License (an open source software license commonly described at http://opensource.org/licenses/MIT).
OPEN-SOURCE CODE. A Submission will be ineligible to win a prize if it was developed using code containing or depending on software licensed under an open source license:
- other than an Open Source Initiative-approved license (see http://opensource.org/licenses); or
- an open source license that prohibits commercial use.
Participant warranties and obligations
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