This paper proposes cross-modal data programming (XMDP) for machine learning (ML) in medicine.
Weakly Supervised Classification of Aortic Valve Malformations Using Unlabeled Cardiac MRI Sequences
This work formalizes a deep learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.
The Role of Massively Multi-Task and Weak Supervision in Software 2.0
Outlining a vision for a Software 2.0 lifecycle centered around the idea that labeling training data can be the primary interface to Software 2.0 systems.
Software 2.0 and Snorkel: Beyond Hand-Labeled Data
This paper describes Snorkel, a system that enables users to help shape, create, and manage training data for Software 2.0 stacks.