Search Results for author: Okyaz Eminaga

Found 3 papers, 0 papers with code

Biologic and Prognostic Feature Scores from Whole-Slide Histology Images Using Deep Learning

no code implementations21 Oct 2019 Okyaz Eminaga, Mahmood Abbas, Yuri Tolkach, Rosalie Nolley, Christian Kunder, Axel Semjonow, Martin Boegemann

Histopathology is a reflection of the molecular changes and provides prognostic phenotypes representing the disease progression.

Deep Learning for Prostate Pathology

no code implementations11 Oct 2019 Okyaz Eminaga, Yuri Tolkach, Christian Kunder, Mahmood Abbas, Ryan Han, Rosalie Nolley, Axel Semjonow, Martin Boegemann, Sebastian Huss, Andreas Loening, Robert West, Geoffrey Sonn, Richard Fan, Olaf Bettendorf, James Brook, Daniel Rubin

For case usage, these models were applied for the annotation tasks in clinician-oriented pathology reports for prostatectomy specimens.

Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis

no code implementations24 Aug 2019 Okyaz Eminaga, Mahmoud Abbas, Christian Kunder, Andreas M. Loening, Jeanne Shen, James D. Brooks, Curtis P. Langlotz, Daniel L. Rubin

A well-fitted PlexusNet-based model delivered comparable classification performance (AUC: 0. 963) in distinguishing prostate cancer from healthy tissues, although it was at least 23 times smaller, had a better model calibration and clinical utility than the comparison models.

General Classification

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