Clustering of PSA Data for Prostate Cancer Risk Classification and Its Explainability (2022)
ETH
Abstract Prostate cancer is the most common malignancy affecting men and thesecond-leading cause of cancer death in the US. To detect and classify the risk of prostate cancer, doctors perform screening of prostate-specific antigen (PSA) levels. In this Thesis we want to improve thisrisk classification with unsupervised machine learning methods, as thelabels of cancer or no cancer may not reflect the truth; given that canceris only considered as such after confirmation by biopsy and thus possi-bly leaving some patients with cancer with the wrong label.