Fig. 2

The receiver operator characteristic curves for predicting breast cancer using chromosomal scale length variation with machine learning algorithms. We used a subset of the UK Biobank dataset consisting of 5925 women (1534 who had been diagnosed with breast cancer and 4391 who had never been diagnosed with any form of cancer). We partitioned this group into a training and test set. We used the training set to train algorithms to recognize differences in chromosomal scale length variation data between the women with breast cancer and those without. We then tested this algorithm on the test set. We repeated this process multiple times with different training/test set partitions and found that the AUC was 0.836 with a 95% confidence interval of 0.830 to 0.843