Methods of assessing breast cancer using machine learning systems
AssigneeAgendia N.V.
InventorsBastiaan Van Der Baan, Annuska Maria Glas
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Abstract
The present disclosure provides methods and systems using machine learning to assess one or more of a patient's biomarkers to analyze various conditions, including cancers, such as breast cancer. The present systems and methods can be trained to analyze patient's biomarker data to form prognoses, diagnoses, and treatment suggestions. Further, the present systems and methods can use biomarker feature data and clinical feature data to create novel correlations in order to provide more accurate, patient-specific diagnoses, prognoses, and treatment suggestions.
Claims19
A method of analyzing breast cancer, the method comprising:
- training an analysis system to associate expression signatures with clinical outcomes;
- determining expression levels of RNA molecules in a blood sample from a patient;
- producing, from the determined expression levels, an RNA signature associated with said sample;
- providing the signature as input to the trained analysis system;
- and
- operating the analysis system to assess disease.
An analysis method comprising:
- providing training data to an analysis system, the training data comprising gene expression signatures and image data with known patient outcomes;
- training the analysis system to correlate the gene expression signatures with the image data;
- measuring RNA expression levels from a patient blood sample and providing the measured expression levels as input to the trained analysis system;
- and
- operating the analysis system to assess disease based on learned correlations between gene expression signatures and the image data.
Dependencies are inferred from the claim text.