Thank you so much to everyone who submitted their executive summary drafts by the midpoint deadline. It was great to see how people are engaging with the challenge, and we were glad to see some final submissions for both the main challenge track describing existing data and for the Ideas for Data Collection
Below, we provide general feedback and guidance on building strong submissions based on the midpoint submissions. As you prepare your submissions, be sure to follow these tips and to leverage the resources and guidance provided in the problem description.
- Data for early detection
- Confirm that your data meet the challenge requirements for usability. Closely review the problem description, paying attention to sections on data access requirements and what you will need to deliver if your submission is selected for a prize. Feel free to ask if you aren’t sure how the requirements apply to your data.
- Review the challenge structure and goals. The overall challenge series aims to identify and develop better methods for prediction of Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD) as early as possible. This first phase of the challenge is focused on sourcing shareable datasets that can support novel machine learning approaches for predicting AD/ADRD as early as possible, with an emphasis on addressing biases in existing data sources. Strong submissions will describe data that can be used for prediction of early AD/ADRD, is machine-learning ready, can be publicly shared, and addresses biases in existing data sources.
- Submit an idea for data collection if you have an idea about challenge-relevant data that would not be deliverable for this challenge. The primary goal of the challenge is to find an existing dataset, but solvers may have ideas for collecting or collating datasets relevant to the challenge. Proposals and datasets that would not be available for sharing by the finalist delivery deadline for this challenge can be submitted as an idea for data collection.
- Executive summary write-ups
- Provide a description of your dataset. Your executive summary should include basic descriptive information about your dataset. For example, a reader should be able to learn how much data there is from how many patients, and what kinds of variables are in the data. It should be clear that the data are suitable for use in the challenge, and any restrictions on sharing due to data sensitivity or copyright should be disclosed.
- Define and provide a clear rationale for your target variable. 20% of your score will be determined by how clearly and well you make a case for the use of your target variable. The target variable is your operationalization of AD/ADRD and it would serve as the ground truth label for future predictive modeling. It should be clear in your executive summary which variable is your target variable. Your executive summary should also include a rationale for the use of that target variable as a ground-truth measure of AD/ADRD.
- Describe and justify your predictor variables. 20% of your score will be determined by the potential for your predictor data to provide a useful signal for early prediction of AD/ADRD. Include a justification for your predictor variables in your executive summary, for example by listing the potential benefits of using your predictor variables to detect early AD/ADRD relative to standards used today.
- Submission requirements and formatting
Mind the submission requirements. In your final submissions, adhere to the submission requirements. Your executive summary should be 1 page (excluding references) and should provide a concise overview. Use your data description (maximum of 6 pages, excluding references) to provide full detail.
Draw on the recommended template. We have provided templates for structuring your submission using subheadings that relate to the evaluation criteria. The templates include information from the problem description and are designed to help you build a competitive submission. You can strengthen your submission by using these templates, making sure that you directly address every component listed for each subheading, and uploading accompanying files relevant to components of your submission (e.g., data use agreements, IRB approval notices, data management plans).