HOW CAN WE HELP YOU? Call 1-800-TRY-CHOP
In This Section
RESCHEDULED: Maximize the Value of Labeled Data at CHOP for AI/ML
United States
We are excited to launch the Arcus Annotation Initiative, which is a central repository for annotated clinical notes and other unstructured data. This initiative aims to maximize the impact of our labeling efforts by enabling CHOP researchers to easily share, access, and build upon existing annotations.
Labeled or annotated data is essential for training and evaluating effective machine learning (ML) and artificial intelligence (AI) models, but producing it can be time-consuming and expensive. By creating shared Annotation Libraries of high-quality labeled data, we can accelerate the development and evaluation of ML/AI solutions across diverse research projects.
Join us for a session that will provide an overview of the Arcus Annotation Initiative, explain the importance of annotated data, showcase ongoing annotation projects, and outline how you can contribute and benefit from this valuable resource. Experts from Arcus’s Applied Data Science and Library Science teams will present.
Speakers
Scott Haag, PhD
Supervisor, Applied Data Science
Maryam Daniali, PhD
Data Scientist
Allison Olsen, MSc, MA
Digital Archivist
Jennae Luecke, MSLS
Data Discovery and Catalog Librarian