Enhancing precision medicine using topological data analysis: a study on myocardial infarction patients

Every year, about 805,000 people suffer from acute myocardial infarction (AMI) in the United States. Precision medicine aims to identify and treat subgroups of patients, which requires their accurate classification. While traditional classification is done based on the knowledge of clinicians, automated classification using data analysis may offer an improvement. However, popular algorithms like k-means clustering require that the number of clusters in the dataset are pre-specified.