Efficient learning from big data for cancer risk modeling: A case study with melanoma.
Journal:
Computers in biology and medicine
Published Date:
Apr 30, 2019
Abstract
BACKGROUND: Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance. We present a case study of a cloud-based approach to learning from de-identified electronic health record data and demonstrate its effectiveness for melanoma risk prediction.