University of Rochester Biomedical Data Science Hackathon Summer 2020

Data are now live.

Logistics

0. Registration is open until 5PM Sunday. Teams can consist of up to 4 people. Register by using the google form.
1. You may add team members up to noon EDT on 8/11 by editing your response to the google form or emailing the organizers.
2. Teams of entirely undergraduates will be in the undergraduate division, else they will be in the open division.
3. Predictions on test data set are submitted by pushing to github. A respository with the name Hackathon-Summer-2020, owned by the team captain, will be queried for a file named prediction/prediction.csv. If the team captain forks this repository and writes predictions there everything should work (as long as the predictions are formatted correctly).
4. Predictions will be scored at least once daily, starting 8/8, with scores posted by noon. At the organizers' option, predictions may be scored more frequently than this.
5. General questions/problems can be directed to issues page. We encourage other hackathon participants to respond to issues.
6. The scoreboard is located here, and will be updated starting noon on 8/8. We cannot provide support beyond the diagnostic output included on the scoreboard if an error is encountered in scoring your predictions.

Data

• Training data are here. These data include the labels that you need to predict
• Test data are here. Your predictions should be in the order of the subject_ids listed here -- no join is performed on the subject_id column.

Data Description

These data are from a prospective multi-year clinical translational study including three cohorts of term infants experiencing their first Respiratory Syncytial Virus (RSV) season. All infants are less than or equal to nine months of age at study entry. The three subject cohorts represent the full spectrum of RSV disease severity and include a birth cohort, a cohort of infants hospitalized for RSV disease and infants evaluated at ambulatory settings for RSV infection. All infants are followed longitudinally and evaluated at recognition of acute RSV infection and twice during convalescence. Genome-wide expression is assessed in the nasal airways (nasal_gene_expr), and in sorted peripheral blood lymphocytes(cd4_gene_expr, cd8_gene_expr, and cd19_gene_expr). Additionally, the microbiome of the nasal airway was measured (nasal_microbiome). All five of these data modalities are hypothesized to contribute to the severity of the disease, measured by a Global Respiratory Severity Score (GRSS), which is the prediction target for this challenge.

Prizes

1. First place in each division: $300 + $50*(team size)
2. Second place: 0 + $50*(team size)
3. In addition, members of teams whose submissions outperform random guessing will be entered into a lottery for $20 grubhub giftcards. Up to 30 will be awarded.
4. Predictions will be scored based on mean square error, lower values are better.

Scoreboard