Mayo Foundation for Medical Education and Research

Decipher Biosciences, Inc.

Veracyte Sd, Inc.

Genomedx Biosciences Inc.

Anamaria Crisan

Robert B Jenkins

Elai Davicioni

Nicholas Erho

Ismael A Vergara Correa

Mercedeh Ghadessi

Christine Buerki

Nicholas George Erho

In some embodiments, a machine learning model may be accessed and used to generate a likelihood score related to a condition. In some embodiments, pre-computed vectors may be derived from a training dataset used to build the machine learning model, and the pre-computed vectors may be used to generate processed data from target data derived from a target sample. The machine learning model may then be used on the processed data to generate the likelihood score related to the condition. As an example, subsets of the training dataset may be randomly selected, and the pre-computed vectors may be derived from the randomly-selected subsets of the training dataset. The pre-computed vectors may be applied to the target data to generate the processed data. In one use case, for example, the target data may be normalized using the pre-computed vectors.

Systems and methods for preprocessing target data and generating predictions using a machine learning model

Disclosed herein, in certain instances, are methods, systems and kits for the diagnosis, prognosis and determination of cancer progression of a cancer in a subject. Further disclosed herein, in certain instances, are methods, systems and kits for determining the treatment modality of a cancer in a subject. The methods, systems and kits comprise expression-based analysis of biomarkers. Further disclosed herein, in certain instances, are probe sets for use in assessing a cancer status in a subject.

Cancer diagnostics using biomarkers

Growing community of inventors

Vancouver, Canada

Anamaria Crisan