Abstract: |
In some aspects, the described systems and methods provide for a method for training a model to predict survival time for a patient. The method includes accessing annotated pathology images associated with a first group of patients in a clinical trial. Each of the annotated pathology images is associated with survival data for a respective patient. Each of the annotated pathology images includes an annotation describing a tissue characteristic category for a portion of the image. Values for one or more features are extracted from each of the annotated pathology images. A model is trained based on the survival data and the extracted values for the features. The trained model is stored on a storage device. |
Inventor: |
Beck, Andrew H. (Brookline, MA, US); Khosla, Aditya (Watertown, MA, US) |
Applicant: |
PathAI, Inc. (Boston, MA, US) |
Face Assignee: |
PathAI, Inc. (Boston, MA, US) |
Filed: |
2018-06-06 |
Issued: |
2020-05-12 |
Claims: |
20 |
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US10650929
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1. A method for training a model to predict survival time for a patient, the method comprising:
(5)
(8)
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8. A system for training a model to predict survival time for a patient, the system comprising:
(5)
(2)
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15. A non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform:
(5)
(8)
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