Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning

Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning

The annotation of large datasets is often the bottleneck in the successful application of artificial intelligence in computational pathology. For this reason recently Multiple Instance Learning (MIL) and Semi Supervised Learning (SSL) approaches are gaining popularity because they require fewer anno...

Full description

Bibliographic Details
Main Authors: Arne Schmidt, Julio Silva-Rodriguez, Rafael Molina, Valery Naranjo
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Cancer classification
histopathology
multiple instance learning
semi-supervised learning
whole slide images
Online Access:https://ieeexplore.ieee.org/document/9681818/

Internet

https://ieeexplore.ieee.org/document/9681818/

Similar Items