arxivcs.LGq-bio.QM2026-07-21
An unsupervised clustering analysis of breast cancer data derived from electronic health records enhanced through UMAP dimensionality reduction
Davide Chicco, Nicoletta Benvenuto
Breast cancer is one of the most widespread types of cancer, affecting approximately 8 million women worldwide. Electronic health records of patients diagnosed with this disease can serve as valuable datasets for computational analyses, enabling the discovery of new insights abou…