Data Challenges

In July 2023, we changed our name from AACC (short for the American Association for Clinical Chemistry) to the Association for Diagnostics & Laboratory Medicine (ADLM). The following page was written prior to this rebranding and contains mentions of the association’s old name.

Artery Challenges

The Association for Diagnostics & Laboratory Medicine’s (formerly AACC) Data Analytics Steering Committee created a series of data challenges on the Artery. The challenges are a chance to learn and share data analytics skills with like-minded colleagues. You can submit an answer to these challenges or ask a question about them at any time. The Association for Diagnostics & Laboratory Medicine (ADLM) membership is required to access Artery posts.

Predicting PTHrP Results

In collaboration with the Informatics Section of the Department of Pathology and Immunology at Washington University School of Medicine, the ADLM Data Analytics Steering Committee invited competitors to develop an algorithm that predicts a patient's PTHrP result using laboratory data available at the time of order. The winning team was invited to share their approach during the ADLM Informatics Division luncheon at the 2022 AACC Annual Scientific Meeting.

See the competition description and download the dataset to test your own skills at Kaggle.

Read more about the competition and meet the winners in CLN.

In this video, Yingheng Wang describes the winning team's approach to predicting PTHrP results.

Help with Hemolysis

In collaboration with the Informatics Section of the Department of Pathology and Immunology at Washington University School of Medicine, the ADLM Data Analytics Steering Committee invited competitors to develop an algorithm to rank blood specimen collectors based on how much money could be saved over the following year if they are trained on how to prevent sample hemolysis. The winning team was invited to share their approach at a scientific session during the 2023 ADLM Annual Scientific Meeting.

See the competition description and download the dataset to test your own skills at Kaggle.