Abstract: Methods and systems are provided herein for automatically determining blood lactate levels. The method can comprise receiving bio-signal data associated with a patient; processing the bio-signal data to extract one or more bio-signal data features; generating a tensor dataset comprising the one or more bio-signal data features; and processing the tensor dataset using a machine learning model to generate an estimated blood lactate level.

Abstract: A method for solving the supervised machine learning problem. A supervised machine learning algorithm is provided with training examples and is capable of classifying new measurements as belonging to one of the groups it was trained on. The proposed supervised learning technique has a single parameter controlling the test's bias in favour of one of the groups it was trained on. The technique can be used to solve a wide array of problems.

Abstract: This document presents a computational metric which can form a component of a computer-aided detection algorithm applied to magnetic resonance imaging examinations.