Deep learning for prostate cancer
Title: Deep learning for prostate cancer
SNIC Project: Berzelius-2021-47
Project Type: LiU Berzelius
Principal Investigator: Eduard Chelebian Kocharyan <eduard.chelebian@it.uu.se>
Affiliation: Uppsala universitet
Duration: 2021-09-17 – 2022-04-01
Classification: 30203
Homepage: https://tissuumaps.research.it.uu.se/
Keywords:

Abstract

The goal of the project is to predict whether a patient will develop prostate cancer in the future based on prostate needle biopsies. For that, we have a database of biopsies that were deemed benign at time=0. However, some of them developed cancer in a span of 2 years (label=1), while others did not even after 10 years (label=0). The deep learning techniques provided below could help prognostication and see if the physician missed the malignancy or if there was something else that indicated that a particular patient would develop cancer.