Ultrasonic wake-up system
    42.
    发明授权

    公开(公告)号:US12257458B2

    公开(公告)日:2025-03-25

    申请号:US18325982

    申请日:2023-05-30

    Abstract: The present application provides an ultrasonic wake-up system. The system includes an ultrasonic imaging device, an ultrasound stimulation device, and an ultrasound stimulation effect evaluation device, and acquires an ultrasonic image of a target object through the ultrasonic imaging device, transmits an ultrasound to the target object based on the ultrasonic image through the ultrasound stimulation device, and adjusts the transmitted ultrasound required through the ultrasound stimulation effect evaluation device. Therefore, peripheral nerves are accurately stimulated, an uplink reticular wake-up system is activated, so as to wake up patients with disorders of consciousness.

    Methods and apparatuses for training magnetic resonance imaging model

    公开(公告)号:US12190568B2

    公开(公告)日:2025-01-07

    申请号:US17889189

    申请日:2022-08-16

    Abstract: Methods and apparatuses for training a magnetic resonance imaging model, electronic devices and computer readable storage media are provided. A method may include: acquiring a magnetic resonance image data set; constructing a ring deep neural network to be trained; inputting an under-sampled magnetic resonance image and a full-sampled magnetic resonance image respectively to two neural networks included in the ring deep neural network, to generate respective simulated magnetic resonance images; inputting a first simulated full-sampled magnetic resonance image and the full-sampled magnetic resonance image to a pre-constructed first simulated magnetic resonance image class discrimination model, to obtain a first discrimination result indicating whether or not the first simulated full-sampled magnetic resonance image is of a simulated magnetic resonance image class; and adjusting a network parameter of the ring deep neural network based on a preset loss function, to obtain a trained magnetic resonance imaging model.

    DATA ERROR CORRECTION METHOD AND APPARATUS, AND ELECTRONIC DEVICE

    公开(公告)号:US20240419897A1

    公开(公告)日:2024-12-19

    申请号:US18673562

    申请日:2024-05-24

    Abstract: The present application is suitable for the technical field of data processing, and provides a data error correction method and apparatus and an electronic device. The method includes: decoding a base sequence to be subjected to error correction into a first text, the base sequence to be subjected to error correction being composed of a plurality of bases; performing word segmentation on the first text to obtain a plurality of text units; performing error detection on the plurality of text units to obtain a text unit having an error; and performing error correction on the base sequence to be subjected to error correction according to the text unit having the error. By means of the above method, error correction for data can be achieved, and the storage cost of DNA can also be reduced.

    ALZHEIMER'S DISEASE BIOMARKER, AND SCREENING METHOD THEREFOR AND APPLICATION THEREOF

    公开(公告)号:US20240369583A1

    公开(公告)日:2024-11-07

    申请号:US18689508

    申请日:2021-09-16

    Abstract: An Alzheimer's disease biomarker, and a screening method therefor and use thereof. The Alzheimer's disease biomarker is 11(Z), 14(Z)-eicosadienoic acid. The screening method for the Alzheimer's disease biomarker comprises: acquiring samples, testing the samples, and performing structural identification and data analysis on metabolites in the samples, wherein specifically, metabolites in faeces samples can be tested by liquid chromatography-mass spectrometry, to carry out structural identification on the metabolites; and selecting a metabolite showing a difference from the metabolite level of a control group as the Alzheimer's disease biomarker. Using 11(Z), 14(Z)-eicosadienoic acid as an Alzheimer's disease biomarker is of great significance to clinical early diagnosis of Alzheimer's disease; the present invention can be used for preparing a diagnostic tool for Alzheimer's disease, predicting the individual treatment effects of patients with Alzheimer's disease, and preparing drugs for treating Alzheimer's disease.

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