Winners’ Presentation for the NCI CRDC AI Data Readiness Challenge

Join the winners of the NCI Cancer Research Data Commons (CRDC) Artificial Intelligence (AI) Data Readiness Challenge as they present their solutions for improving the AI readiness of NCI CRDC data and components.

Tier 1 (training an AI/ML model with single modal data)

• 1^st Place: Jennifer Blasé (Ruvos)
  • Project: “Gene expression-based prediction of treatment response in ovarian cancer”
• 2^nd Place: Agnes McFarlin
  • Project: “Identifying cancerous lung nodules without the presence of annotated slides for reference”

Tier 2 (training an AI/ML model with multi-modal data)

• 1^st Place: Abhishek Jha (Elucidata)
  • Project: “Distinguishing primary tumor from normal solid tissue in lung squamous cell carcinoma”
• 2^nd Place: Jeff Van Oss (BAMF Health)
  • Project: “Predicting Von Hippel-Lindau mutation in kidney tumors using radiomic features”

The challenge offered participants up to $50,000 in total prizes to help NCI assess the AI data-readiness of CRDC data and components. Participants defined AI data-readiness metrics and used those to pre-process data from one or more data commons for AI/ML model training. Results from the challenge will help the CRDC meet the needs of AI-based research.