METHODS FOR TRAINING AND USING A MACHINE LEARNING MODEL FOR PREDICTING A LIKELIHOOD OF AN EVENT OCCURRING IN A PATIENT HAVING A MALIGNANT TUMOUR
Abstract
Methods for training and using a machine learning model for predicting a likelihood of an event occurring in a patient having a malignant tumour are provided. The method of using the machine learning model includes inputting a pathology image of a portion of a malignant tumour of a patient and one or more categorical risk factors associated with the malignant tumour or the patient. The method also includes extracting, from the pathology image, one or more features relating to one or more properties of the malignant tumour. The method further comprises determining a predicted likelihood of an event occurring in the patient based on the extracted features and the one or more categorical risk factors. The method additionally includes outputting the predicted likelihood.
Inventors 4
- Sarah Volinsky-Fremond Aachen author as filed: Fremond, Sarah Corinne Margot
- Tjalling Bosse Aachen author as filed: Bosse, Tjalling
- Nanda Horeweg Aachen author as filed: Horeweg, Nanda
- Viktor Hendrik Koelzer Aachen author as filed: Koelzer, Viktor Hendrik
Inventors are linked to an Aachen author when surname and first name match exactly one author.
Applicants
- University of Zurich
- Academisch Ziekenhuis Leiden (h.o.d.n. LUMC) GBS Leiden
- Univ Zuerich
Cited papers 2 in the database
Non-patent literature as cited (3)
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