Abstract: This application provides a method and apparatus of analyzing the ECG frequency parameters with applications for the diagnosis of ST-segment elevation myocardial infarction (STEMI) diseases, which relates to the interdisciplinary field of biomedical and science engineering. The method includes obtaining ECG signals from subjects through the designed electrodes; calculating ECG frequency domain parameters of the subjects based on the proposed power spectrum model and getting the analytical validation results after studying and verifying the parameters; generating indicators based on the analytical validation results, which could be potentially used as alternative indicators for STEMI diagnosis; and alerting when the indicators meet preset abnormal conditions. The present embodiment is a powerful tool to diagnose STEMI diseases faster and more effectively and helps patients receive timely assistance and treatment.

Abstract: Disclosed are bifunctional targeted protein autophagy degraders that comprise: 1) a small-molecule targeting a protein of interest; 2) a linker; and 3) a small-molecule recruiter of the autophagy adapter LC3B. These degraders target specific proteins for degradation through the autophagy-lysosomal degradation pathway.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same for the inhibition of CRBN, and the treatment of CRBN-mediated disorders.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same.

Abstract: The present invention relates to a wireless multi-modal tonoarteriogram (TAG) monitoring apparatus and system based on nail sensing. The invention relates to the field of blood pressure monitoring technology. The nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus comprises a nail patch, a plurality of sensors and a processing module, at least one first sensor of the plurality of sensors is arranged on the nail patch, the plurality of sensors are used for obtaining a biological signal at a fingernail; the processing module is used for obtaining a target physiological parameter according to the biological signal at fingernail, with the target physiological parameter comprising a central tonoarteriogram signal.

Abstract: Aspects of the invention include detecting an error alert from a target computer system. In response to detecting the error alert, performance data is then retrieved from the target computer system. A gated recurrent unit (GRU) neural network is used to generate a prediction of a root cause of the error alert based on the performance data. The weights of a reset gate of the GRU neural network are adjusted based on received feedback of the prediction.

Abstract: The present disclosure provides a technical solution of multi-modal chatting, which may provide response to user query by using multi-modal response in the interaction between chatbot and human beings, so that the expressing ways and the expressed content by the chatbot could be richer by using such response in a multi-modal way.

Abstract: The present invention is related to a compound represented by the following structural formula: The present invention is also related a method of treating a subject with a disease which can be ameliorated by inhibition of aminocarboxymuconate semialdehyde decarboxylase (ACMSD).

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same.

Abstract: The present invention relates to method and apparatus for heart-level blood pressure estimation based on ensemble learning. The invention relates to the technical field of biomedical technology. The method comprises: acquiring radial arterial blood pressure related information and a hydrostatic pressure of the radial artery of a subject; performing blood pressure conversion based on the radial arterial blood pressure related information and the hydrostatic pressure of the radial artery to obtain at least two brachial arterial blood pressure values; inputting the at least two brachial arterial blood pressure values into a trained correction model to obtain a target brachial arterial blood pressure value. The present invention realizes the conversion from a peripheral blood pressure, such as a radial arterial blood pressure measured by a wearable device, to a heart-level blood pressure, i.e.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same for the inhibition of CRBN, and the treatment of CRBN-mediated disorders.

Abstract: The present invention relates to a wearable apparatus for continuous monitoring of physiological parameters. The invention relates to the field of physiological parameters monitoring technology. The wearable apparatus for the continuous monitoring of physiological parameters comprises an earring body and a monitoring device; wherein the monitoring device comprises a sensor module, the sensor module being arranged at the earring body for obtaining a biological signal at an auricle; the biological signal is to be inputted to a pre-built physiological system model or a deep machine learning model to obtain a physiological parameter; the physiological parameter comprising tonoarteriogram (TAG) signals. The invention realizes the convenience of wearing by a user without affecting normal activities of the user, further allows performing of a long-term monitoring of the user and improving monitoring accuracy while reducing damages to the skin of the ear.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same.

Abstract: The present invention provides a deep learning-based wearable electro-tonoarteriography method and apparatus for the estimation of continuous arterial blood pressure, which relates to the technical fields of medical detection and artificial intelligence, and is applicable to, such as, tonoarteriogram (TAG, which is continuous arterial blood pressure) signal estimation and cardiac diseases detection. The method comprises: acquiring at least one lead ECG signal collected from a clothing and/or a wearable device worn by a subject of detection; processing the ECG signal based on a deep learning network, determining a signal processing result related to a tonoarteriogram information and/or related to a cardiac disease information. The present invention is advantageous in realizing the acquisition of continuous arterial blood pressure signal and/or the automatic diagnosis of cardiac disease on the basis of ensuring accuracy.

Abstract: The present invention relates to an AI-enhanced wearable photo-electro-tonoarteriography (PETAG) method and apparatus. The invention relates to the technical fields of medical detection and artificial intelligence, and is applicable to, such as, tonoarteriogram (TAG) signal estimation, which is continuous blood pressure and cardiac diseases detection. The method comprises: acquiring at least one lead electrocardiogram (ECG) signal and multi-wavelength photoplethysmogram signals (MWPPG signals); processing the ECG signal and the MWPPG signals by a multimodal model-based multi-task learning network, determining a signal processing result related to a TAG information and/or related to a cardiac disease information. The present invention is advantageous in reducing computational cost involved in signal processing on the basis of ensuring accuracy.

Abstract: The present invention provides a method and a device for calibrating a blood pressure estimation model for determining tonoarteriogram (TAG) signals, which relates to a cross field between biomedicine and scientific engineering.

Abstract: The present invention provides a method, a device, an electronic apparatus and a computer-readable storage medium for adaptive blood pressure monitoring and model training. The invention relates to the technical field of medical monitoring. The method of adaptive blood pressure monitoring comprises: acquiring a radial arterial blood pressure measurement and a hydrostatic pressure of a radial artery; inputting the radial arterial blood pressure measurement and the hydrostatic pressure into a trained blood pressure conversion model, obtaining a brachial arterial blood pressure value according to the blood pressure conversion model by performing the following operations: weighting the hydrostatic pressure according to a conversion function of the blood pressure conversion model to obtain a weighted hydrostatic pressure; determining the brachial arterial blood pressure value according to the radial arterial blood pressure measurement and the weighted hydrostatic pressure.

Abstract: The present invention provides compounds, compositions thereof, and methods of using the same.

Abstract: The present invention relates to a multi-modal sensor module, comprising an electrode base, an insulating film sheet, a functional layer and a protective film; the protective film is used for isolating external environment with a side away from the functional layer for use in contacting surface of biological tissues; the functional layer comprises a substrate and at least one sensor module provided in isolation in the substrate; a side of the electrode base away from the insulating film sheet is used for contacting surface of the biological tissues; the multi-modal sensor module is in a state of collecting electrocardiogram (ECG) signal, a side of the protective film away from the functional layer and a side of the electrode base away from the insulating film sheet are both for contacting surface of the biological tissues, so that the protective film, the biological tissues and the electrode base form an ECG signal collection path.