Abstract:
An automated method and system are provided for receiving an input of flow cytometry data and analyzing the data using a hierarchical arrangement of analytical elements, each of which utilizes a support vector machine to automatically classify the data into different subpopulations to recognize a pattern within the data. The pattern may be used to generate a diagnostic prediction for a patient or to identify patterns within samples collected from multiple subjects.
Abstract:
The present disclosure provides methods of detecting and determining the aggressiveness of prostate cancer. These methods can be used to determine whether or not a patient needs a biopsy as well as guide treatment selection.