609 results about "Heart disease" patented technology

The dynamic monitoring system for the senile cardiac patient comprises a multi-mode sensor module, a data processing module, an analysis module and an alarm module. The multi-modal sensor module collects parameters to generate a multi-modal physiological signal; the data processing module generates a preprocessing signal; the analysis module performs real-time analysis on the pre-processed signal based on a preset elderly electrocardiogram characteristic model to generate a graded alarm instruction; the alarm module triggers corresponding local reminding, remote notification or first-aid linkage response according to the graded alarm instruction, wherein the first-aid linkage response automatically sends the patient position and key physiological data to a specified first-aid center through the first-aid communication module; wherein the self-adaptive adjustment of the multi-mode sensor module comprises the step of dynamically optimizing signal gain according to a skin contact state. According to the dynamic monitoring system for the senile cardiac patients, the problems that dynamic monitoring of the senile cardiac patients is poor in real-time performance, high in false alarm rate and delayed in first-aid response can be solved.

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.

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 invention relates to the technical field of heart data analysis, in particular to an AI (artificial intelligence)-based heart disease prediction system, which comprises a feature relationship modeling module for mapping each type of information into a multi-dimensional feature space based on collected heart data, analyzing the condition correlation degree between feature nodes, connecting the feature nodes through correlation information, and establishing a model; and quantifying a linkage effect between the features to obtain a feature condition dependency relationship analysis result. According to the method, various types of heart health data are noded by constructing a multi-dimensional feature space, and a correlation structure is established according to condition correlation among data features. And a synergistic effect and an interdependence relationship among the features are disclosed. By analyzing the joint state probability of the feature nodes, the linkage effect of the feature combination on the overall risk is quantified, and the analysis depth of the disease risk is enhanced. In addition, by comparing the independent state probability of a single feature with the joint state probability of the feature combination, a feature combination that makes a significant contribution to the risk can be identified.

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 belongs to the technical field of medical image recognition, and particularly discloses a myocardial infarction complication recognition method based on a heart multi-modal image, and the method comprises the steps: firstly obtaining multi-modal medical image data and corresponding diagnosis report text data; constructing a myocardial infarction complication identification model; dividing the whole network into a feature extraction stage and an image text feature matching stage by adopting a separation training thought, carrying out back propagation on the network in the feature extraction stage through L1 loss, and optimizing weight parameters of the feature extraction network; performing back propagation on the network in the image text matching stage by comparing loss, and optimizing parameters of an image and a text encoder; and finally, collecting a medical image of the heart of a patient, inputting the medical image into the trained myocardial infarction complication identification model, and generating a character diagnosis report of heart disease complication. Therefore, early automatic diagnosis of myocardial infarction complications is realized.

The invention relates to a heart organoid and an in-vitro preparation method thereof, and belongs to the technical field of stem cells. The invention provides a heart organoid. The heart organoid is obtained by induced culture of an adherent pluripotent stem cell mass; the adherent pluripotent stem cell mass is obtained by adherent culture of a suspended pluripotent stem cell mass; the suspension pluripotent stem cell mass is obtained by suspension culture of pluripotent stem cells. According to the in-vitro preparation process of the heart organoid, after pluripotent stem cells form balls, the pluripotent stem cell balls are subjected to staged induced differentiation under adherent culture, so that cell subtypes such as epicardial cells and the like can be generated without additional addition or additional stimulation of signal channels, and the heart organoid is more homogeneous. The self-occurring multi-lineage coexisting heart organoid can better simulate biological events derived from multiple cell types and multiple cell subtypes in the early development process of an embryonic heart, and has great application prospects in exploration of pathogenic factors and potential treatment targets of congenital heart diseases.

The invention discloses a heart disease prediction system based on an electrocardiosignal and a large model, and relates to the field of electrocardiosignal processing, and the system is characterized in that the electrocardiosignal of a user is collected by using a heart coat, and baseline offset suppression and noise processing operation are carried out on the electrocardiosignal by using a data processing center; a variability sequence is extracted from the processed electrocardiosignal, an electrocardiograph scatter diagram is drawn according to variability, and scatter points in the scatter diagram are numbered and coded in a partitioned mode to obtain the sequence information entropy of the heart rate variability sequence; segmenting the electrocardiosignal based on the sequence information entropy and the wave crest, obtaining a waveform segment of a single cardiac pulse according to a segmentation result, inputting the waveform segment into the large medical prediction model, and outputting the characteristic change of the electrocardiosignal; and comparing the feature change with a pre-stored disease feature standard and outputting a disease prediction result. According to the method, the complex characteristics of the electrocardiosignals and the prediction capacity of the large model are combined, and the diagnosis precision and the early-stage discovery rate of heart diseases can be remarkably improved.

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 piRNA marker for diagnosing and evaluating myocardial aging, a kit and application of the piRNA marker. The application of the miRNA marker comprises one or more of the following applications: A1) application in preparation of a product for diagnosing myocardial aging; a2) in preparation of products for screening myocardial aging; a3) in preparation of a product for treating myocardial aging; a4) in preparation of myocardial aging condition assessment products; a5) in preparation of products for identifying and distinguishing myocardial aging and other heart diseases; the piRNA marker is piR-hsa-014388, and the nucleotide sequence of the piRNA marker is as shown in SEQ ID No. 1. The expression quantity of the piRNA marker provided by the invention in the plasma of a myocardial aging patient is obviously increased compared with that of a healthy control person, which indicates that the piR-hsa-014388 has the potential to be used as the myocardial aging biomarker.

The invention discloses a multi-mode-based flexible wearable heart function monitoring method, system and device, and relates to the technical field of health monitoring, and the method comprises the steps: outputting a multi-mode signal through a flexible patch sensing module when the flexible patch sensing module is arranged in a detection area; wherein the flexible patch sensing module comprises an electrocardio sensor, a pulse wave sensor, a heart sound sensor, a strain sensor and a microfluidic biosensor. According to the invention, high-precision synchronous signal acquisition is realized through flexible patch integrated multi-modal sensing, heart multi-source signal features are adaptively extracted in combination with a multi-scale convolutional neural model, and timing sequence relevance is captured by using a bidirectional long-short-term memory network, so that the accuracy and reliability of heart disease diagnosis are remarkably improved, and the accuracy and reliability of heart disease diagnosis are improved. Meanwhile, non-invasive and continuous monitoring and early pathological screening are supported.

The invention discloses a characteristic value calculation method based on electrocardio data, belongs to the field of medical data analysis, and provides an electrocardio data analysis and processing method. Comprising the following steps: decomposing different frequency components of an electrocardiosignal by using wavelet transform, and analyzing on different time scales. Wavelet transformation is relatively suitable for detecting QRS wave groups, and due to the fact that the wavelet transformation can highlight transient characteristics of signals on different frequency bands, complex electrocardiosignal processing is more efficient. In addition, wavelet transform is not only suitable for wave crest detection, but also can help to remove signal noise and improve signal definition. The deep learning technology is used for automatically extracting the features from the electrocardiosignals, a feature extractor does not need to be manually designed, related medical professional knowledge and the artificial intelligence technology are combined, wave crests in the electrocardiosignals can be more accurately detected, and meanwhile anomaly detection can be carried out, such as early signs of heart diseases such as sinus arrhythmia and the like.

This invention is eyewear (e.g. eyeglasses) with electrodes (e.g. EEG sensors) which collect brain activity data (e.g. electroencephalographic data) which can be used to predict and / or detect health events (e.g. epileptic seizure, stroke, or heart attack) or function as a BCI (Brain-to-Computer Interface) for communication. There can be anterior and posterior electrodes on the eyewear temple and the temple can have an upward and / or inward curving wave or arm. A posterior electrode can have multiple electroconductive protrusions to help penetrate between strands of hair.

The invention discloses application of fisetin or a salt thereof in medicine preparation, the compound is used for treating or preventing obesity cardiomyopathy, preferably heart diseases caused by hyperlipidemia, but is not limited to the inducer, and specifically, the medicine can inhibit or improve various obesity cardiomyopathy.

The invention relates to the technical field of medical data processing, in particular to a construction method and system for a cardiology nursing knowledge base. The system is used for performing mapping relation analysis of heart states and nursing knowledge according to heart pathology data and corresponding heart nursing data, and generating a heart state nursing relation feature matrix; performing pathological mode identification processing of heart state nursing relation characteristics on the heart state nursing relation characteristic matrix to generate a pathological mode heart state nursing relation characteristic matrix; based on the pathological mode heart state nursing relation feature matrix, an optimized prediction model of heart pathological mode and nursing information derivation is designed, and an optimized heart nursing derivation prediction model is generated; and performing intelligent feedback engine design processing of the cardiology nursing knowledge base based on the optimized heart nursing derivation prediction model so as to construct an intelligent cardiology nursing knowledge base engine. According to the invention, efficient and intelligent cardiac nursing knowledge base establishment is realized.

The invention provides conveying equipment for surgical interventional therapy of congenital heart diseases, and belongs to the field of medical equipment. Comprising a guide pipe, a traction pipe and a conveying pipe, the upper end and the lower end of the guide pipe are open, the conveying pipe is located in the traction pipe, a sealing plate is fixedly connected to the lower end of the inner surface of the guide pipe and makes sliding contact with the outer surface of the traction pipe, and a conveying assembly is arranged at the upper end of the conveying pipe; the conveying assembly comprises a fixing sleeve fixedly connected with the upper end of the outer surface of the conveying pipe. By arranging the conveying assembly, a support is clamped and fixed through a contact plate, the support is stored and placed in a guide pipe, a good protection effect on the support in the conveying process can be achieved, and therefore the probability that the support falls off accidentally in the conveying process can be reduced; and therefore, the stability and the safety of the conveying equipment in the working process can be effectively improved.

The invention provides a Mongolian medicine composition capable of nourishing blood and cardiac muscle, relaxing chest, diminishing swelling and inhibiting Bada dry Heray as well as a preparation method and application of the Mongolian medicine composition, and belongs to the technical field of Mongolian medicines. The Mongolian medicine composition provided by the invention is prepared from the following raw materials: fructus choerospondiatis, nutmeg, tabasheer, flos carthami, pomegranate, fructus crataegi, fructus tribuli, cluster mallow fruit, folium rhododendri daurici, fructus piperis longi, fructus tsaoko and fructus amomi rotundus. The Mongolian medicine composition provided by the invention has the effects of nourishing blood and cardiac muscle, inhibiting Badaozhi, relaxing chest and diminishing swelling, can be applied to treatment of chronic cardiac insufficiency, pulmonary heart disease, dilated heart disease and various edema, and can achieve a remarkable treatment effect.

The invention relates to the technical field of electrocardiosignal analysis, and discloses a long-sequence electrocardiosignal disease recognition system based on a Transform architecture. The core defects that in traditional electrocardiogram analysis, waveform integrity is damaged by fixed window segmentation, a lead space topological relation is neglected, and long sequence modeling efficiency is low are overcome, a P-QRS-T waveform structure is completely reserved through the heart beat adaptive segmentation technology, and the fixed window truncation risk is eliminated; the lead anatomical topology and the space-time coding are fused, and multi-lead electrophysiological association is modeled; long sequence efficient processing is realized based on hierarchical sparse Transform, and the recognition sensitivity of complex pathologies such as arrhythmia and myocardial ischemia is improved; in combination with gradient directional regulation and control and a streaming processing mechanism, the clinical real-time requirement is met while the diagnosis accuracy is guaranteed, and finally, reliable, efficient and universal intelligent decision support is provided for early warning of heart diseases through lightweight deployment of an adaptive mobile terminal.

To provide methods and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning methods and systems.SOLUTION: There are provided systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosing a patient such that stenting and other procedures may be applied during a single session in the catheter lab.SELECTED DRAWING: Figure 1C

This document provides devices and methods for the treatment of heart conditions, hypertension, and other medical disorders. For example, this document provides devices and methods for treating atrial fibrillation by performing thoracic vein ablation and / or electroporation procedures, including pulmonary vein myocardium ablation. In some embodiments, the ablation and / or electroporation is delivered in differing areas in and / or around the pulmonary vein in coordination with each other for enhanced efficacy.

In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Systems and methods and devices are provided for treating conditions such as heart failure and / or pulmonary hypertension by at least partially occluding flow through the superior vena cava for an interval spanning multiple cardiac cycles. A catheter with an occlusion device is provided along with a controller that actuates a drive mechanism to provide at least partial occlusion of the patient's superior vena cava, which reduces cardiac filling pressures, and induces a favorable shift in the patient's Frank-Starling curve towards healthy heart functionality and improved cardiac performance. The occlusion device may include a lumen obstructed by a relief valve that may permit fluid flow through the occlusion device to release an excessive build-up of pressure.

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 relates to an electrocardiogram monitoring method and device, a storage medium and electronic equipment, and relates to the technical field of electrocardiogram, and the method comprises the following steps: obtaining a target portrait of a to-be-monitored user; according to the target portrait, determining at least one suitable fitting part during electrocardiogram monitoring; determining an actual electrocardiogram of the to-be-monitored user based on each suitable fitting part, and judging whether the actual electrocardiogram is an abnormal electrocardiogram or not; if yes, acquiring actual symptoms of the to-be-monitored user, and determining whether the to-be-monitored user has a heart disease hidden danger or not based on the actual symptoms, target heart problems easily occurring when the electrocardiogram of the to-be-monitored user is abnormal and easily accompanied symptoms corresponding to each target heart problem; if it is determined that the heart disease hidden danger exists, targeted heart disease early warning is sent out. The method has the effect of improving the accuracy of electrocardiogram monitoring.

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.

The invention discloses an integral forming method of a myocardial chip embedded with nanofibers and a flexible circuit board, which adopts integral forming equipment, integrates a photocuring part and an electrostatic spinning part, and realizes collaborative operation through an upper computer and a driving device; the method comprises the following steps: firstly, forming a lower runner layer by adopting a hydrogel material through a photocuring component, and embedding a flexible circuit board into the top of the lower runner layer; forming a nanofiber bracket on the flexible circuit board by adopting a spinning material through the electrostatic spinning part; a hydrogel material is printed on the nanofiber support to form an upper flow channel layer, flow channel packaging is achieved, and efficient transmission of electrical stimulation and field potential signals is achieved through a flexible circuit board. According to the method, the problems of low alignment precision, strong manual dependence and insufficient automation degree in the traditional process are solved, the chip manufacturing efficiency and consistency are improved, and a detection platform with high integration level and high biocompatibility is provided for drug screening and heart disease research.

The invention discloses a construction method and application of a hypercongenital heart disease-pulmonary arterial hypertension model, which better simulates children with the congenital heart disease in Yunnan by adopting the conditions of lateral anastomosis of aorta abdominalis and inferior vena cava and hypoxia feeding, and makes a new contribution to the research of pulmonary arterial hypertension. In the experimental shunt + hypoxia group and the monocrotaline + hypoxia group, the heart of the SD rat has the change of pulmonary arterial hypertension, four cases in the shunt + hypoxia group have tricuspid regurgitation, and the rest experimental rats have no tricuspid regurgitation.

The invention provides a heart-targeted nano-liposome delivery carrier, a circular RNA (Ribonucleic Acid) medicine for treating cardiovascular diseases as well as a preparation method and application of the circular RNA medicine, and belongs to the technical field of biomedicine. The heart-targeted nano-liposome delivery carrier comprises saccular nano-liposome particles and heart-targeted peptide CMP (chemical mechanical polishing) modified on the surfaces of the nano-liposome particles, the amino acid sequence of the heart targeting peptide CMP is shown as SEQ ID NO: 6. The heart-targeted nano-liposome delivery carrier has a good heart-targeted effect, and the nano-liposome delivery carrier is used as a delivery tool to accurately deliver a circular RNA drug to a heart part, so that the effect of treating cardiovascular diseases (such as cardiac hypertrophy) is greatly improved; a new treatment mode is provided for clinical treatment of cardiovascular diseases, and the purpose of efficiently preventing and treating heart diseases is achieved.

The invention discloses a pyrimidinedione derivative as well as a preparation method and application thereof. Molecules of the pyrimidinedione derivative have better myosin inhibitory activity, also have antioxidant effects of DPPH and / or MDA and the like and anti-ferroptosis activity, and can be applied to treatment / prevention of heart myosin, anti-oxidative stress and anti-ferroptosis mechanism related diseases. The diseases or symptoms mainly comprise hypertrophic cardiomyopathy, diastolic heart failure, left ventricular hypertrophy, heart diseases with pathophysiological characteristics related to the hypertrophic cardiomyopathy, or other disease states and conditions which are obvious to those skilled in the art, or a prodrug thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof, or a pharmaceutically acceptable salt thereof. Or a hydrate or solvate thereof, and a pharmaceutical composition containing the same.

The present invention relates to a D-galactopyranose compound of formula (1)whereinthe pyranose ring is α-D-galactopyranose, and these compounds are high affinity galectin-1 and / or galectin 3 inhibitors for use in treatment of inflammation; fibrosis; scarring; keloid formation; aberrant scar formation; surgical adhesions; septic shock; cancer; metastasising cancers; autoimmune diseases, metabolic disorders; heart disease; heart failure; pathological angiogenesis; eye diseases; atherosclerosis; metabolic diseases; diabetes type I; diabetes type II; insulin resistance; Diastolic heart failure; asthma; liver disorders.