Abstract PD6-03: Clinical-Grade Detection of Breast Cancer in Biopsies and Excisions Using Machine Learning

Feb 15, 2021·
Matthew G. Hanna
,
Patricia Raciti
,
Ran A. Godrich
,
Adam Casson
,
Julian Viret
,
Donghun Lee
,
Matthew C. H. Lee
Alican Bozkurt
Alican Bozkurt
,
Philippe Mathieu
,
Brandon Rothrock
,
Thomas J. Fuchs
· 0 min read
Abstract
We present a clinical-grade machine learning system for detecting breast cancer in biopsies and excisions. The system was developed and validated on a large dataset of whole slide images and demonstrates performance comparable to experienced pathologists.
Type
Publication
In Cancer Research 81(4 Supplement), PD6-03 (2021)
publication
Computational Pathology Breast Cancer Deep Learning
Alican Bozkurt
Authors
Alican Bozkurt
AI Scientist
I am an AI Scientist at Paige AI. I did my Ph.D. with Jennifer Dy, Dana Brooks, and Jan-Willem van de Meent at Northeastern University. My main research interests are machine learning with emphasis on probabilistic programming, deep neural networks, and their applications in biomedical image processing. I am one of the developers of Probabilistic Torch, a library for deep generative models that extends PyTorch. I am also one of the maintainers of the PyTorch distributions module.