Systems and methods for processing electronic images to identify transplant donor-recipient matches
AssigneePaige.AI, Inc.
InventorsJeremy Daniel KUNZ, Christopher KANAN
Life of this patent
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Abstract
Systems and methods are described herein for processing electronic medical images to predict one or more donor recipients for a patient. For example, a digital medical image of the patient may be received, wherein the patient is in need of a transplant. A trained machine learning system may be determined. The digital medical image may be provided into the trained machine learning system, the trained machine learning system determining a patient embedding. Using the patient embedding, a subset of donor recipients may be determined. Based on the subset of donor recipients a recommendation of optimal donors may be determined.
Claims20
A computer-implemented method for processing electronic medical images to predict one or more donor recipients for a patient, comprising:
- receiving a digital medical image of the patient, wherein the patient is in need of a transplant;
- determining a trained machine learning system;
- providing the digital medical image into the trained machine learning system, the trained machine learning system determining a patient embedding;
- determining, using the patient embedding, a subset of donor recipients;
- and
- determining based on the subset of donor recipients a recommendation of optimal donors.
A system for processing electronic medical images to predict one or more donor recipients for a patient, the system comprising:
- at least one memory storing instructions;
- and
- at least one processor configured to execute the instructions to perform operations comprising:
- receiving a digital medical image of the patient, wherein the patient is in need of a transplant;
- determining a trained machine learning system;
- providing the digital medical image into the trained machine learning system, the trained machine learning system determining a patient embedding;
- determining, using the patient embedding, a subset of donor recipients;
- and
- determining based on the subset of donor recipients a recommendation of optimal donors.
A non-transitory computer-readable medium storing instructions that, when executed by a processor, perform operations processing electronic medical images to predict one or more donor recipients for a patient, the operations comprising:
- receiving a digital medical image of the patient, wherein the patient is in need of a transplant;
- determining a trained machine learning system;
- providing the digital medical image into the trained machine learning system, the trained machine learning system determining a patient embedding;
- determining, using the patient embedding, a subset of donor recipients;
- and
- determining based on the subset of donor recipients a recommendation of optimal donors.
Dependencies are inferred from the claim text.