SYSTEMS AND METHODS FOR GENERATING ACCURATE OPHTHALMIC MEASUREMENTS

    公开(公告)号:US20230031527A1

    公开(公告)日:2023-02-02

    申请号:US17870304

    申请日:2022-07-21

    Applicant: Alcon Inc.

    Abstract: Certain aspects of the present disclosure provide an ophthalmic measurement device. The device comprises one or more ophthalmic measurement features, configured to generate a measurement for an anatomical characteristic of an eye of a patient, and a user interface, configured to enable a medical practitioner to interact with the ophthalmic measurement device and a memory. The device also comprises a hardware processor configured to: determine whether the measurement satisfies measurement criteria based on comparing the measurement with the measurement criteria, upon determining that the measurement does not satisfy the measurement criteria, cause the one or more ophthalmic measurement features to generate a new measurement for the anatomical characteristic, determine whether the new measurement satisfies the measurement criteria based on comparing the new measurement with the measurement criteria, and, upon determining that the new measurement satisfies the measurement criteria, cause the user interface to display the new measurement.

    SELECTION OF INTRAOCULAR LENS BASED ON A PREDICTED SUBJECTIVE OUTCOME SCORE

    公开(公告)号:US20210369106A1

    公开(公告)日:2021-12-02

    申请号:US17330327

    申请日:2021-05-25

    Applicant: Alcon Inc.

    Abstract: A system and method for selecting an intraocular lens, for implantation into an eye, includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute a machine learning model trained with a training dataset. Execution of the instructions by the processor causes the controller to obtain pre-operative objective data for the patient, including one or more anatomic eye measurements. The controller is configured to obtain pre-operative questionnaire data for the patient, including at least one personality trait. The pre-operative objective data and the pre-operative questionnaire data are entered as respective inputs to the machine learning model. A predicted subjective outcome score for the patient is generated as an output of the machine learning model. The intraocular lens is selected based in part on the predicted subjective outcome score.

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