Abstract: Disclosed is an electronic device for predicting sarcopenia, which includes a memory and a processor connected with the memory to execute instructions included in the memory. The processor extracts a first result value as output data for a first machine learning model by using an eye image of a subject as input data for the first machine learning model and determines whether sarcopenia of the subject occurs based on the first result value. The first result value includes an MRD1 value of the subject corresponding to the eye image, an upper eyelid edge location change value, an eye closing speed value, and an eye opening speed value.

Abstract: A method of predicting the anterior chamber angle of the eye of a surgical candidate for lens implantation according to an embodiment of the present invention includes obtaining input data including a lens size, obtaining a predicted postoperative anterior chamber angle based on a learning model using the input data. The learning model may be trained based on the lens size and the measured postoperative anterior chamber angle of a plurality of patients who have undergone the lens implantation in the past.

Abstract: An electronic device for predicting myopia regression, which includes a memory and a processor connected with the memory to execute instructions included in the memory. The processor collects first target data of a subject and second target data of the subject, extracts a first result value as output data for a first machine learning model by using the first target data as input data for the first machine learning model, and determines whether there is a possibility of myopia regression of the subject based on the first result value.

Abstract: The present invention relates to a method for recommending a vision correction surgery, and the method according to one aspect of the present invention comprises: obtaining an examination data of a subject; predicting whether the vision correction surgery is suitable for the subject from the examination data; when the vision correction surgery is suitable for the subject, predicting whether the vision correction surgery using a laser is available for the subject from the examination data; when the vision correction surgery using the laser is available for the subject, calculating corneal shape factor prediction values of the subject after a standard vision correction surgery and a custom vision correction surgery from the examination data; and when the vision correction surgery using the laser is available for the subject, suggesting a vision correction surgery corresponding to the subject from the examination data.

Abstract: The present disclosure is a user interface providing method for multi-party schedule management including transmitting, by the processor, a schedule management interface in which individual schedules of a plurality of users are arranged to a user device through a communication interface connected thereto, receiving, by the processor, a schedule registration request related to a first user among the plurality of users obtained from the schedule management interface through the communication interface, from the user device, determining, by the processor, a second user who is available for schedule registration, among the plurality of users, according to a type of the scheduler registration request and registering, by the processor, a cooperative schedule including the first user and the determined second user in the schedule management interface output through the display of the user device.

Abstract: A method for determining a lens and apparatus using the method are disclosed. According to an embodiment, a method for determining a lens to be inserted into an eyeball during lens implant surgery using machine learning may be provided, the method comprising: obtaining a plurality of examination data of a person to be operated on; and determining a size of a lens to be inserted into an eyeball of the person among a plurality of lens sizes by inputting the obtained plurality of examination data of the person to a lens determination model, wherein the lens determination model is different from a formula for determining a lens to be inserted into an eyeball during lens implant surgery, and is trained based on examination data of patients who have had lens implant surgery in the past and size information of lenses inserted into eyeballs of the patients.

Abstract: A method for determining a lens and apparatus using the method are disclosed. According to an embodiment, a method for determining a lens to be inserted into an eyeball during lens implant surgery using machine learning may be provided, the method comprising: obtaining a plurality of examination data of a person to be operated on; and determining a size of a lens to be inserted into an eyeball of the person among a plurality of lens sizes by inputting the obtained plurality of examination data of the person to a lens determination model, wherein the lens determination model is different from a formula for determining a lens to be inserted into an eyeball during lens implant surgery, and is trained based on examination data of patients who have had lens implant surgery in the past and size information of lenses inserted into eyeballs of the patients.

Abstract: The present invention relates to a method for recommending a vision correction surgery, and the method according to one aspect of the present invention comprises: obtaining an examination data of a subject; predicting whether the vision correction surgery is suitable for the subject from the examination data; when the vision correction surgery is suitable for the subject, predicting whether the vision correction surgery using a laser is available for the subject from the examination data; when the vision correction surgery using the laser is available for the subject, calculating corneal shape factor prediction values of the subject after a standard vision correction surgery and a custom vision correction surgery from the examination data; and when the vision correction surgery using the laser is available for the subject, suggesting a vision correction surgery corresponding to the subject from the examination data.

Abstract: The present invention relates to a method for recommending a vision correction surgery, and the method according to one aspect of the present invention comprises: obtaining an examination data of a subject; predicting whether the vision correction surgery is suitable for the subject from the examination data; when the vision correction surgery is suitable for the subject, predicting whether the vision correction surgery using a laser is available for the subject from the examination data; when the vision correction surgery using the laser is available for the subject, calculating corneal shape factor prediction values of the subject after a standard vision correction surgery and a custom vision correction surgery from the examination data; and when the vision correction surgery using the laser is available for the subject, suggesting a vision correction surgery corresponding to the subject from the examination data.

Abstract: A method for determining a lens and apparatus using the method are disclosed. According to an embodiment, a method for determining a lens to be inserted into an eyeball during lens implant surgery using machine learning may be provided, the method comprising: obtaining a plurality of examination data of a person to be operated on; and determining a size of a lens to be inserted into an eyeball of the person among a plurality of lens sizes by inputting the obtained plurality of examination data of the person to a lens determination model, wherein the lens determination model is different from a formula for determining a lens to be inserted into an eyeball during lens implant surgery, and is trained based on examination data of patients who have had lens implant surgery in the past and size information of lenses inserted into eyeballs of the patients.

Abstract: The present invention relates to a method for recommending a vision correction surgery, and the method according to one aspect of the present invention comprises: obtaining an examination data of a subject; predicting whether the vision correction surgery is suitable for the subject from the examination data; when the vision correction surgery is suitable for the subject, predicting whether the vision correction surgery using a laser is available for the subject from the examination data; when the vision correction surgery using the laser is available for the subject, calculating corneal shape factor prediction values of the subject after a standard vision correction surgery and a custom vision correction surgery from the examination data; and when the vision correction surgery using the laser is available for the subject, suggesting a vision correction surgery corresponding to the subject from the examination data.