Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers.

Objectives: Prediction of prostate cancer pathological stage is an essential step in a patient's pathway. It determines the treatment that will be applied further. In current practice, urologists use the pathological stage predictions provided in Partin tables to support their decisions.

Visual scan paths in first-episode schizophrenia and cannabis-induced psychosis.

Objective: Patterns of successive saccades and fixations (scan paths) that are made while viewing images are often spatially restricted in schizophrenia, but the relation with cannabis-induced psychosis has not been examined. We used higher-order statistical methods to examine spatiotemporal characteristics of scan paths to determine whether viewing behaviour was distinguishable on a continuum.

Methods: Patients with early acute first-episode paranoid schizophrenia (SCH; n = 11), cannabis-induced psychosis (CIP; n = 6) and unaffected control subjects (n = 22) undertook a task requiring free viewing of facial, fractal and landscape images for 5 seconds while their eye movements were recorded.