209 results about "Heart disease" patented technology

A computer implemented method for training a whole medical image foundation model, including: receiving a plurality of medical image datasets; extracting local sections of image data from the plurality of medical image datasets; obtaining one or more causal variables associated with the local sections and / or patient; training one or more self-supervised learning models based on the local sections of image data and the causal variables; combining the one or more trained self-supervised learning models with a deep learning network configured to combine a latent representation of the local sections of image data from the one or more trained self-supervised learning models into a patient-level representation; and combining, with the one or more trained self-supervised learning models and the deep learning network, at least one further network or function configured to accept the patient-level representation as input, the at least one further network or function operable to perform one or more patient-specific prediction tasks.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The invention discloses an electrocardiosignal preprocessing system and method based on filtering and deep learning, and relates to the field of electrocardiosignal data processing. The multi-stage adaptive filtering module comprises a baseline drift elimination unit, a power frequency interference suppression unit and a myoelectricity noise removal unit, and all the units are connected in sequence to form pipelined parallel processing; the deep learning fusion module is used for performing deep feature extraction and noise classification on the output signal and feeding back a classification result to the multi-stage adaptive filtering module; the signal quality evaluation module carries out quality evaluation on the electrocardiosignals subjected to multi-stage adaptive filtering and deep learning fusion and judges whether the signal quality is qualified or not; a feature enhancement and standardization module; the technical effects of improving the self-adaptability and robustness, improving the calculation efficiency of heart disease classification, the signal fidelity and the diagnosis reliability, and enhancing the signal quality evaluability and the self-adaptive ability are achieved.

The invention discloses a hierarchical OvO-SVM nondestructive testing method for the attack degree of potato blackheart disease, which comprises the following steps: preparing a detection sample, and collecting a VIS / NIR original transmission spectrum; preprocessing the collected original spectrum; adopting a random forest algorithm to screen sensitive wavebands; a two-stage hierarchical classification framework is constructed, health / disease coarse classification-disease degree subdivision is carried out, cross validation type Platt calibration is carried out on decision scores of each group of SVMs, and corresponding probabilities are output; according to the method, a classification threshold value is introduced, the final grade of the morbidity degree is judged through the maximum value of a pseudo probability / threshold value, and through the technical path of spectrum preprocessing, sensitive band screening, two-stage hierarchical modeling, probability calibration and classification threshold value shaping, hierarchical modeling and OvO local boundary learning are utilized to judge the morbidity degree. According to the method, the boundary confusion problem of'health-light 'and'moderate-heavy' is remarkably relieved, the spectrum dimension is reduced by screening sensitive wavebands, and accurate grading of the attack degree of the blackheart disease is achieved.

The invention provides a training method of a CT and DSA real-time automatic fusion registration system for structural heart disease intervention and a storage medium. The training method comprises the following steps: establishing a registration system data set; establishing an initial registration system; based on the registration system data set, training an initial registration system to obtain a trained CT and DSA intraoperative registration system; and inputting the preoperative CT image data and the intraoperative real-time DSA image data of the person to be identified into the trained CT and DSA intraoperative registration system to obtain an intraoperative real-time fusion navigation image and intraoperative risk graphical prompt information. According to the method, cross-modal and cross-time-point dynamic registration can be realized, higher-precision intraoperative navigation support is provided for structural heart disease intervention, the operation safety is improved, and radiation exposure is reduced.

A prosthetic heart valve for the treatment of structural heart disease wherein the prosthetic heart valve includes an expandable frame that a) has an open cell geometry in the frame of the prosthetic heart valve that can be used to reduce delivery system size, b) has high radial strength, c) has improved restoration of the physiologic EOA, d) has lower recoil, e) has little or no longitudinal foreshortening, f) allows for proper placement of the bioprosthetic valve in relation to the native commissures of the valve, h) has symmetrical and cylindrical expansion of the prosthetic valve resulting in lower rates of leaflet thrombosis and structural valve deterioration, and / or i) prevents allergic response and restenosis associated with nickel content.

The invention relates to the technical field of health monitoring, in particular to an electrocardiograph monitoring intelligent diagnosis system based on deep learning and multi-modal fusion technology, which is characterized in that a multi-modal synchronous sensing unit synchronously acquires ECG, PCG and PPG data streams with aligned timestamps, and an edge intelligent diagnosis unit operates a lightweight model with the parameter smaller than 1MB, so that the ECG monitoring intelligent diagnosis system is obtained. The cloud fusion analysis unit is used for dynamically fusing multi-source data by adopting a cross-modal attention mechanism to generate a ventricular fibrillation probability PVF, and the dynamic collaborative decision-making unit is used when R is equal to III or Cilt, and the cloud fusion analysis unit is used for dynamically fusing the multi-source data by adopting a cross-modal attention mechanism to generate a ventricular fibrillation probability PVF; deep diagnosis, PVFgt, is triggered within 5 seconds at 0.9; and when 0.95, a third-level audible and visual alarm is triggered, and the closed-loop optimization unit continuously optimizes the model by distilling and compressing the misdiagnosis sample. According to the intelligent diagnosis system for electrocardiograph monitoring, rapid edge diagnosis is achieved through a lightweight model, critical cases can respond rapidly through cloud cooperation, and the accuracy and timeliness of heart disease diagnosis are improved.

This invention discloses a cardioprotective compound composition and its preparation based on improving the absorption rate of coenzyme Q10, relating to the fields of pharmaceuticals and functional foods. The core active ingredients of this composition consist of coenzyme Q10, vitamin E, and black pepper extract, with a specific mass ratio range for each. It can also be combined with pharmaceutically acceptable carriers and antioxidant synergists to prepare various oral formulations. This invention, through the construction of a ternary active component with a specific ratio, achieves in vivo synergistic effects on absorption promotion and antioxidant regeneration, solving the technical problems of low oral bioavailability and insufficient accumulation of myocardial-targeted activity in existing coenzyme Q10 preparations. It significantly improves the conversion efficiency of coenzyme Q10 into a usable active form for cardiomyocytes and can be widely applied in the preparation of drugs and functional foods for the prevention or treatment of heart diseases.

The present application relates to the field of microbiological technology, and particularly relates to a pathogenic bacterium causing root rot symptoms of red heart disease of Astragalus membranaceus and application thereof, the pathogenic bacterium is Fusarium sp. Fusarium sp. FUS-001-2025, preserved in China General Microbiological Culture Collection Center on March 16, 2026, with the preservation number of CGMCC No. 42529; it is determined to be a new recorded strain of Fusarium sp. through morphological and molecular identification, and the bactericide sensitivity determination shows that 25% silthiofam·prochloraz has the strongest inhibition effect, 25% bromothalonil, 50% azoxystrobin and 70% methylthiophanate have significant inhibition at high concentrations. The present application provides an important pathogenic bacterium resource for the pathogenic mechanism, disease resistance evaluation and development of control agents of red heart disease of Astragalus membranaceus.

The utility model relates to the technical field of interventional medical instrument in-vitro simulation demonstration, in particular to a structural heart disease interventional medical instrument in-vitro simulation demonstration device. The device comprises a model fixing device (3), a heart model (31) and a detachable valve leaflet model (32) are fixed on the model fixing device (3), a camera (5) is further arranged on the device, and the device can be used for simulation device demonstration of heart valve intervention medical instrument in-vitro performance research, instrument operation training of an operator in vitro and operation process practice.

The invention relates to a heart disease patient health intelligent monitoring system. The system comprises a medical data acquisition module, a data preprocessing module, a feature extraction model construction module, a monitoring model construction module and a health monitoring module. According to the invention, original data is obtained through data acquisition; a data preprocessing method including space-time alignment, key event extraction, knowledge graph construction, irregular sampling processing and data set segmentation is adopted; an integrated learning model is adopted as a feature extraction model, and through multi-modal feature extraction and a dynamic weight distribution mechanism, the discrimination ability of feature expression is remarkably improved, and the limitation of processing a complex medical scene by a single model is overcome; an improved graph convolution model is adopted as a monitoring model, through dynamic construction of relation topology and injection of domain knowledge, in combination with a time decay mechanism and nonlinear monitoring activation design, time sequence dependence of health risk evolution and asymmetric cost characteristics of medical decision are captured, and the reliability of health monitoring is improved.

The invention belongs to the technical field of medical information processing, and particularly discloses a regression model establishment method and system for detecting related indexes of myocardial cells of Wuzhishan pigs by using blood biochemical indexes, and the method comprises the following steps: collecting blood and heart tissue samples of the Wuzhishan pigs at different month ages, detecting the blood biochemical indexes including liver function, blood fat and blood sugar indexes, and establishing a regression model for detecting the related indexes of myocardial cells of the Wuzhishan pigs. Related indexes of myocardial cells; analyzing the index expression quantity difference, and screening significant difference indexes; then calculating the correlation between the remarkably different blood biochemical indexes and myocardial cell related indexes, and determining high-correlation blood biochemical indexes; and finally, constructing a first version of multiple regression model by respectively taking the myocardial enzyme index and the myocardial cell related index as dependent variables and the high-correlation blood biochemical index as an independent variable, removing outliers and updating the sample set on the basis of the first version of multiple regression model, and constructing a second version of multiple regression model by utilizing the new sample set, and on the basis of the second version of multiple regression model, constructing a third version of multiple regression model by adopting a stepwise regression method. According to the method, related indexes of myocardial cells can be accurately deduced through blood biochemical indexes, and support is provided for Wuzhishan pig heart disease research and model animal research and development.

The present application relates to the technical field of medicine, and specifically includes the application of immunosuppressants in the preparation of drugs for treating pulmonary hypoperfusion type congenital heart disease, and further provides a premature infant pulmonary hypoperfusion animal model, and results show that lung development is significantly improved after using immunosuppressants. The present application verifies the Wnt pathway which is critical for lung development, indicates that immunosuppressants can improve the Wnt pathway changes caused by pulmonary hypoperfusion, confirms that immunosuppressants have a therapeutic effect on the pulmonary hypoperfusion type congenital heart disease caused by pulmonary hypoplasia, provides a new method and idea for improving lung development of such children, and thereby improves the long-term survival quality of congenital heart disease children in China.

The invention provides a radiofrequency ablation instrument for treating heart diseases, and relates to the technical field of medical equipment. The radiofrequency ablatometer comprises a man-machine interaction device, a data processing device, a radiofrequency energy generating device, an ablation device, an ablation parameter acquisition device, a twelve-lead ECG signal acquisition device, an ultrasonic image acquisition device, a vital sign monitoring acquisition device and a circulating cooling device which are respectively connected with the radiofrequency energy generating device and the ablation device, the cooling device is used for supplying cooling liquid to the ablation device; the data processing device controls power output of the radio frequency energy generating device according to the twelve-lead ECG signals and ablation parameters, and the man-machine interaction device displays ultrasonic images, vital sign parameters and ECG data. According to the invention, concentrated display and linkage analysis of ultrasonic images, twelve-lead ECG signals and vital sign parameters are realized for the first time, and the device can be widely applied to percutaneous intracardiac radiofrequency ablation treatment of hypertrophic cardiomyopathy, cardiac tumor and other diseases, and has extremely high clinical application value.

The disclosure provides systems, methods, and non-transitory computer readable media for non-invasively assessing cardiac pressure and efficiency. An example computer implemented method includes: receiving patient-specific image data of a cardiac chamber of a patient, the patient-specific image data acquired from an imaging modality over a cardiac cycle; receiving patient-specific vitals data; deriving non-invasive cardiac parameters from the patient-specific image data and the patient-specific vitals data; applying the non-invasive cardiac parameters to a trained model to generate: a total energy output for blood flow out of the cardiac chamber during the cardiac cycle, and a total energy input for blood flow into the cardiac chamber during the cardiac cycle; and generating, in real time, based on a ratio of the total energy output to the total energy input, a patient-specific cardiac efficiency value for the cardiac chamber, the patient-specific cardiac efficiency value classifying a severity of a heart disease of the patient.

The present invention relates to a detection and alert system for a garment (G) and an application module (APP) which comprise means for triggering an on-demand ECG recording, the application module (APP) being configured - to allow the storage of personal and medical data of the patient, as well as of at least one prior reference ECG recording, - to transmit, to a remote interface module (MD), an alert message (ME) containing thus stored personal data and medical data, - the reference ECG recording also stored, and - the on-demand ECG recording that has been performed.

The utility model discloses a horizontal rehabilitation device for heart disease, which comprises a base, an adjustably arranged pedal assembly arranged on one side of the base and a lying table arranged on the other side of the base, the pedal assembly comprises a support arranged on the base, a lapping plate is arranged on the support, and the lapping plate is arranged on the base. A connecting frame capable of adjusting the placing angle is hinged to the lapping plate, and a rotating wheel with a pedal plate is arranged on the connecting frame; a handheld assembly is further arranged on one side of the support and comprises a supporting frame arranged on the support and a traction belt assembly arranged on the supporting frame in an adjustable mode. The rotating wheels with the pedal plates are adjustably arranged to adapt to the leg length of a patient, the traction belt assembly is arranged to be matched with upper limb exercise of the patient, anaerobic exercise of muscle strength is facilitated, comprehensive recovery of the heart after an operation is facilitated, the structure is simple and compact, and use is flexible.

The invention relates to the technical field of biological medicines, in particular to application of a monoclonal antibody in medicines for treating heart diseases related to Alzheimer's disease. According to the application disclosed by the invention, the application range of the lencanamazumab is expanded to prevention and treatment of AD-accompanied heart failure and pathological myocardial remodeling, and a new drug strategy is provided for treatment of patients with AD-associated heart failure or pathological myocardial remodeling.

The present invention provides novel 4-methylsulfone-substituted piperidine / urea compounds useful for the treatment of dilated cardiomyopathy (DCM) and conditions associated with left and / or right ventricular systolic dysfunction or systolic reserve. The synthesis and characterization of the compounds, as well as methods for the treatment of DCM and other forms of heart disease, are described.

To provide a new ultrasonic irradiation device capable of achieving simple operability and being used for treatment of a heart disease.SOLUTION: The ultrasonic irradiation device 100 of the present invention is a flexible sheet-like member attached to the body surface of the chest of a person, and includes at least a probe 10 capable of transmitting ultrasonic waves, and a control unit 11 or a control device 1 that controls the probe 10 to transmit ultrasonic waves from the probe 10 at a predetermined intensity and interval. The widthwise size of the probe 10 in the direction orthogonal to the thickness direction is a size across two ribs and is equal to or larger than the 50mm.SELECTED DRAWING: Figure 5

The present application relates to a culture method and application of cardiac progenitor cells with myocardial and epicardial dual differentiation potential. Specifically, the present application provides cardiac progenitor cells with myocardial and epicardial dual differentiation potential, and provides a culture medium and culture method for inducing human pluripotent stem cells to differentiate into the dual potential cardiac progenitor cells, and further provides a method for differentiating the dual potential cardiac progenitor cells into myocardial cells and / or epicardial cells. The present application provides a new cell model for the development process and principle research of early cardiac lineage, and has a wide application prospect in the field of cell therapy and regenerative medicine related to heart diseases.

Cell populations for the treatment of cardiac diseases and methods of making the same.

The invention discloses a congenital heart disease image classification method and device based on artificial intelligence and clinical features, and the method comprises the steps: obtaining a to-be-classified image, and obtaining a plurality of interested blocks according to the to-be-classified image through a 3D U-net deep convolutional network; inputting the interested image blocks into seven deep convolutional network models to obtain seven corresponding image block segmentation results and a plurality of types in each image block segmentation result; obtaining a specific gravity coefficient value of each image block segmentation result, and performing weighting according to the specific gravity coefficient values so as to determine an overall segmentation result of the to-be-classified image; and determining a plurality of types in the overall segmentation result and corresponding specific features according to the plurality of types in the interested image blocks and the overall segmentation result through a preset image block growth algorithm, and determining the type of the to-be-classified image according to the specific features in the overall segmentation result. According to the invention, the accuracy of congenital heart disease image classification can be improved.

The present application relates to a kind of cardiac magnetic resonance longitudinal relaxation time measurement method, medium and equipment.The measurement method includes the following steps: S1 uses MOLLI sequence respectively before and after scanning contrast;Specifically, in the before and after scanning contrast, by setting different initial inversion time TI, setting 3 groups of LL experiment LL1, LL2, LL3 triggered by continuous ECG, enough relaxation curve sampling points are obtained after fusion;And data is collected at the end of diastole of cardiac cycle, and 1 image is obtained per heartbeat;S2 image processing.This measurement method can realize single-pixel high-resolution T1 mapping under the breath holding of selection data acquisition and multi-LL experiment data fusion, give consideration to high accuracy, high resolution and high efficiency, and have good compatibility and practicality, provide new scheme for early diagnosis of heart disease, lesion quantification and prognosis evaluation, have wide clinical application prospect.

The application belongs to the technical field of model prediction, and relates to an abnormality identification method applied to electrocardiograms and related equipment.The method comprises the following steps: performing a first vector conversion operation on historical electrocardiogram data according to an encoding model to obtain a historical time sequence embedding vector; constructing an initial text prototype and calculating an initial text embedding vector of the initial text prototype according to a contrast learning function and the historical time sequence embedding vector; constructing a model loss function according to the historical time sequence embedding vector and the initial text embedding vector; performing a model training operation on the text prototype according to the model loss function to obtain a target text prototype; receiving electrocardiogram data to be analyzed sent by a user terminal; performing a second vector conversion operation on the electrocardiogram data to be analyzed according to a loss encoding model to obtain a time sequence embedding vector to be analyzed; inputting the time sequence embedding vector to be analyzed into the target text prototype to perform an abnormality identification operation and obtaining an abnormality identification result.The application can greatly improve the prediction accuracy of heart diseases.

The invention discloses a circular non-coding RNA (Ribonucleic Acid) molecule circSENP6 and application thereof. The nucleotide sequence of the circSENP6 is shown as SEQ ID NO. 1. The invention also discloses a preparation method of the circular non-coding RNA molecule circSENP6. The circular non-coding RNA molecule circSENP6 can be used as a diagnostic biomarker for coronary atherosclerosis, is used for biological identification and clinical detection of coronary atherosclerotic heart disease, and can be used for early discovering coronary heart disease patients, reducing the death rate of coronary heart disease and improving the prognosis of patients by using the expression level of the gene for diagnosis. At present, the main diagnosis method for coronary atherosclerotic heart disease has the risks of high operation danger coefficient, large radiation and the like, and by collecting peripheral blood of a patient for detection, the method has the advantages of small trauma, good repeatability and the like, and is easier to accept.

The application discloses a fetal congenital heart disease intervention path reasoning method and system based on atlas enhanced retrieval, and relates to the technical field of medical data processing and intelligent auxiliary decision-making.The application constructs a domain knowledge graph containing anatomical structure, hemodynamics and evolution law, and establishes a graph-text hybrid index; in the reasoning stage, a large language model is used to extract key features of the target fetus and its mother, multi-hop retrieval and subgraph matching are performed in the atlas, and knowledge context with medical logic constraints is obtained; finally, the thinking chain technology is combined to guide the large model to generate a hierarchical intervention path containing prenatal monitoring, perinatal management and postpartum surgery. The application solves the problem that the existing large model has hallucination and lacks time sequence reasoning ability in complex medical decision-making, and improves the accuracy and explainability of the intervention scheme.

The invention provides a 3D culture method for promoting stem cells to be differentiated into cardiac lineage cells. According to the method, four-stage time sequence induction is adopted, wherein in the stage I, BMP4, Activin A and bFGF are used for efficiently inducing the cells into mesoderm in an insulin-free culture medium; in the stage II, DKK1 is used for inhibiting WNT signals to lock the heart pedigree, and VEGF165 is added in the early stage to start cardiac endothelial differentiation; in the stage III, metabolic support is provided for an insulin-containing culture medium, and bilineage maturation is deepened; in the IV stage, bFGF is added to support long-term survival and function maintenance of the cells, and the whole process is carried out in a 3D embryoid body. According to the invention, the cheap RPMI1640 basal culture medium is used for replacing an expensive commercial culture medium, the high-purity heart micro-tissue which can spontaneously beat and contains cardiac muscle and cardiac endothelial cells can be obtained within about 10 days, and an economical and efficient cell source is provided for heart disease research, drug screening and regenerative medicine.

The invention relates to an adenovirus associated virus 9 (AAV9)-based viral particle, for use in a method of treatment of a heart disease, whereby said viral particle is administered to the heart. The invention further relates to a pharmaceutical composition comprising the AAV9-based viral particle, and to methods of producing the AAV9-based viral particle.

The present disclosure provides beating explanted donor hearts from swine, methods of making thereof, and methods of using thereof. The present disclosure further provides methods of treating a disease (e.g., a heart disease) in a human subject in need thereof comprising transplanting of a beating explanted donor heart from swine. The present disclosure also provides medical instruments suitable for transplanting a beating explanted donor heart from swine.