Subtype and grade classification using histopathologic slides

Principal Investigator

Name
Gal Aviram

Degrees
BSc

Institution
Curatio - DL

Position Title
CTO

Email
gal@curatio-dl.com

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCOI-924

Initial CDAS Request Approval
Mar 2, 2022

Title
Subtype and grade classification using histopathologic slides

Summary
In this project, we will develop and train a machine learning algorithm using histopathology images collected by the PLCO study.
Our algorithm is expected to automatically find image features that are correlative with the patient's grade and cancer subtype.
Our models are expected to perform predictions of the grade and cancer subtype of the patient based on the characteristic features that were found.

Aims

Aim 1 - Correlate between morphologic features in histopathology images and the patient's cancer grade using ML algorithms.
We will develop a supervised deep convolutional network that will receive slides containing cancer cells as input and will be trained to predict the slide's grade.
Aim 2 - Correlate between morphologic features in histopathology images and the patient's cancer subtype using ML algorithms. Constructing a model for subtype prediction using histopathology slides.

Collaborators

Prof. Kun-Hsing Yu, Harvard University.