Breast cancer outcome prediction with tumour tissue images and machine learning.

ABSTRACT:

Purpose

Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.

Methods

Utilising tissue microarray (TMA) samples obtained from the primary tumour of patients (N = 1299) within a nationwide breast cancer series with long-term-follow-up, we train and validate a machine learning method for patient outcome prediction. The prediction is performed by classifying samples into low or high digital risk score (DRS) groups. The outcome classifier is trained using sample images of 868 patients and evaluated and compared with human expert classification in a test set of 431 patients.

Results

In univ

SUBMITTER: Turkki R 

PROVIDER: S-EPMC6647903 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature