Automated assessment of immunofixations with deep neural networks

Abstract

The reliable evaluation of immunofixation electrophoresis is part of the laboratory diagnosis of multiple myeloma. Until now, this has been done routinely by the subjective assessment of a qualified laboratory staff member. The possibility of subjective errors and relatively high costs with long staff retention are the challenges of this approach commonly used today.

Keywords

• artificial intelligence
• computer assisted diagnosis
• deep convolutional neural network
• image recognition
• immunofixation
• pattern recognition