SUPPORT APPARATUS, SUPPORT METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING PROGRAM

    公开(公告)号:US20250140365A1

    公开(公告)日:2025-05-01

    申请号:US18692369

    申请日:2022-09-28

    Abstract: A support apparatus capable of efficiently checking whether or not a patient problem is appropriately set is provided. A support apparatus includes a prediction unit, a calculation unit, and an output unit. The prediction unit predicts a patient problem to be dealt with in order to achieve a target of the patient. The calculation unit calculates a matching level between a predicted patient problem and an actual patient problem, the predicted patient problem being a predicted problem of the patient, and the actual patient problem being a problem of the patient that has been actually dealt with for the patient. The output unit performs control so that an alert is output when the calculated matching level is lower than a predetermined first threshold.

    INFORMATION PROVIDING DEVICE, INFORMATION PROVIDING METHOD, AND RECORDING MEDIUM

    公开(公告)号:US20250103953A1

    公开(公告)日:2025-03-27

    申请号:US18565608

    申请日:2023-08-30

    Inventor: Yuki KOSAKA

    Abstract: An information providing device includes a physical information acquisition means that acquires physical information including an attribute, a physical condition, and a goal with respect to the physical condition of a user, a user information acquisition means that acquires information regarding the user including schedule information of the user, a decision means that decides a content of an advice for the goal and a timing of executing the content of the advice based on the physical information and the schedule information, and an output means that outputs the content of the advice and the timing.

    MACHINE LEARNING MODEL GENERATION APPARATUS, MACHINE LEARNING MODEL GENERATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM

    公开(公告)号:US20240047068A1

    公开(公告)日:2024-02-08

    申请号:US18481426

    申请日:2023-10-05

    CPC classification number: G16H50/20

    Abstract: A machine learning model generation apparatus includes: a movement unit that performs movement processing of moving a sample, having an output error of a (t+1)-th order machine learning model with respect to observation data at time t+1 being larger than a predetermined amount, from the target sample group to a source sample group; and a generation unit that generates a plurality of weak learners by using at least observation data of a sample included in the target sample group after the movement processing and a sample included in the source sample group after the movement processing, and generates a t-th order machine learning model, based on at least each of the plurality of weak learners, and a classification error being evaluated, for each of the plurality of weak learners, by using observation data at time t of the sample included in the target sample group after the movement processing.

    MACHINE LEARNING MODEL GENERATION APPARATUS, MACHINE LEARNING MODEL GENERATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM

    公开(公告)号:US20240038394A1

    公开(公告)日:2024-02-01

    申请号:US18481607

    申请日:2023-10-05

    CPC classification number: G16H50/20

    Abstract: A machine learning model generation apparatus includes: a movement unit that performs movement processing of moving a sample, having an output error of a (t+1)-th order machine learning model with respect to observation data at time t+1 being larger than a predetermined amount, from the target sample group to a source sample group; and a generation unit that generates a plurality of weak learners by using at least observation data of a sample included in the target sample group after the movement processing and a sample included in the source sample group after the movement processing, and generates a t-th order machine learning model, based on at least each of the plurality of weak learners, and a classification error being evaluated, for each of the plurality of weak learners, by using observation data at time t of the sample included in the target sample group after the movement processing.

    REHABILITATION PLANNING APPARATUS, REHABILITATION PLANNING SYSTEM, REHABILITATION PLANNING METHOD, AND COMPUTER READABLE MEDIUM

    公开(公告)号:US20220375568A1

    公开(公告)日:2022-11-24

    申请号:US17761288

    申请日:2020-07-29

    Abstract: A rehabilitation planning apparatus, a rehabilitation planning system, a rehabilitation planning method, and a program capable of efficiently creating a rehabilitation plan are provided. A rehabilitation planning apparatus (1) includes a rehabilitation pattern selection unit (2), an ability value prediction unit (3) that predicts a physical ability value after a target patient performs rehabilitation indicated in a selected rehabilitation pattern, a repetition control unit (4) that performs control so that the selection by the rehabilitation pattern selection unit (2) and the prediction by the ability value prediction unit (3) are repeated, and a determination unit (5) that determines a rehabilitation pattern for, among combinations of rehabilitation patterns and physical ability values obtained through the repetition of the selection and the prediction, a combination of which the physical ability value satisfies a predetermined condition as a rehabilitation plan for the target patient.

    REHABILITATION PLANNING APPARATUS, REHABILITATION PLANNING SYSTEM, REHABILITATION PLANNING METHOD, AND COMPUTER READABLE MEDIUM

    公开(公告)号:US20220375567A1

    公开(公告)日:2022-11-24

    申请号:US17761285

    申请日:2020-07-29

    Abstract: A rehabilitation planning apparatus includes: a similarity calculation unit that calculates a degree of similarity between each of a plurality of pieces of past information and target patient information, each of the plurality of pieces of past information being information about a respective one of a plurality of past patients who performed rehabilitation in a past, and the target patient information being information about a target patient; a ranking unit that extracts at least one piece of past information from the plurality of pieces of past information based on the degree of similarity, and ranks the at least one piece of past information according to a predetermined ranking rule; and a determination unit that determines, as a rehabilitation plan for the target patient, a rehabilitation history of the past patient associated with the past information according to a result of the ranking of the pieces of past information.

    SYSTEM FOR REHABILITATION PLANNING USING MACHINE LEARNING

    公开(公告)号:US20250111924A1

    公开(公告)日:2025-04-03

    申请号:US18979785

    申请日:2024-12-13

    Abstract: A rehabilitation planning apparatus, a rehabilitation planning system, a rehabilitation planning method, and a program capable of efficiently creating a rehabilitation plan are provided. A rehabilitation planning apparatus (1) includes a rehabilitation pattern selection unit (2), an ability value prediction unit (3) that predicts a physical ability value after a target patient performs rehabilitation indicated in a selected rehabilitation pattern, a repetition control unit (4) that performs control so that the selection by the rehabilitation pattern selection unit (2) and the prediction by the ability value prediction unit (3) are repeated, and a determination unit (5) that determines a rehabilitation pattern for, among combinations of rehabilitation patterns and physical ability values obtained through the repetition of the selection and the prediction, a combination of which the physical ability value satisfies a predetermined condition as a rehabilitation plan for the target patient.

    INFORMATION PROCESSING DEVICE
    20.
    发明公开

    公开(公告)号:US20240249842A1

    公开(公告)日:2024-07-25

    申请号:US18420890

    申请日:2024-01-24

    Inventor: Yuki KOSAKA

    CPC classification number: G16H50/20

    Abstract: An information processing device 100 of the present disclosure includes: an acquisition unit 121 that acquires a model that is generated for each elapsed period, and has learned by machine learning to output a measure for a human by receiving input of a plurality of types of feature value representing a condition of the human; a collection unit 122 that collects first output that is obtained when a predetermined number of types of feature value are input to the model of each elapsed period, and second output that is obtained when some types of feature value in the predetermined number of types of feature value are input to the model of each elapsed period; and a setting unit 123 that sets, on the basis of the first output and the second output, types to be associated with the model of each elapsed period. Thereby, the information processing device 100 can be used for assistance of decision-making by a user, or the like.

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