232 results about "Hyperpiesis" patented technology

The invention discloses a hypertensive heart disease early screening system fusing ultrasonic multiple parameters, which comprises the following steps: acquiring ultrasonic image data and physiological index monitoring parameters of a patient at different time points, performing difference comparison on heart structure parameters to generate time sequence change data, and establishing a multi-dimensional data fusion scheme based on the time sequence change data and physiological indexes; according to the fusion scheme, acute risk trigger factors are identified, blood flow abnormal parameters are generated, and emergency threshold comparison is carried out to generate acute risk early warning signals; extracting a myocardial strain degradation rate to determine a chronic degradation acceleration time point, carrying out disease progress stage association to generate a chronic risk layering curve, and establishing a clinical index comparison table; carrying out double-layer correlation on the acute risk early warning signal and the chronic risk layering curve, and carrying out calibration judgment to generate a comprehensive risk judgment sequence; the sequence is decomposed into an acute judgment layer and a chronic judgment layer, a risk threshold value is configured to generate an instant early warning signal, a layered screening report is formed, and technical support is provided for early discovery of the hypertensive heart disease.

The invention provides a hypertensive nephropathy prediction method based on multi-model fusion screening characteristics. An important feature set influencing the occurrence of hypertensive nephropathy is screened based on a multi-model fusion method, and a hypertensive nephropathy prediction model based on multi-model fusion is established by using the feature set. Early screening work for hypertension people is realized, so that the risk of hypertensive nephropathy can be found as early as possible, timely treatment is realized, and the prognosis of patients is improved.

The invention provides an intelligent processing method, system, equipment and medium for high-risk and newly-onset definite diagnosis crowds of hypertension, and belongs to the technical field of hypertension detection.The method comprises the steps that patient examination data are collected and serve as an original data set; preprocessing the original data; constructing a corresponding parameter group; mapping the family history score into a risk quantification function through a dynamic weight coefficient Wi; summing the product of the dynamic weight coefficient Wi and the quantization function Fi to obtain a total risk score; determining whether the patient is a high-risk population based on the diagnosis code and the total risk score; and pushing the high-risk crowd data to a management center server. According to the method, the data is accurately pushed to a corresponding platform or a storage library, so that safe and effective utilization of the data is guaranteed, and sharing and collaboration of regional medical data are realized.

The invention provides an apnea syndrome detection method and device, computer equipment and a medium, and belongs to the field of medical analysis, and the method comprises the steps: constructing a TMNet neural network model which comprises an input layer, a convolution layer, an LSTM module, a full connection layer and an output module which are connected in sequence, a Dropout regularization technology, a ReLU activation function, normalization and a 1 * 1 convolution operation are integrated in the convolution layer; acquiring a physiological signal of a common OSAS patient as source domain data, and acquiring a physiological signal of a special OSAS patient as target domain data; the source domain data and the target domain data are input into the TMNet neural network model for training, and a respiration monitoring model is obtained; and inputting the target physiological signal into the respiration monitoring model to obtain the physiological signal characteristics of the to-be-monitored OSAS patient. The domain adaptation method is used for solving the data distribution difference between the source domain and the target domain, data dependence on special OSAS patients is reduced, and the breathing state of the special OSAS patients such as heart diseases or hypertension can be accurately monitored according to physiological signals of the special OSAS patients.

The invention relates to the field of gene detection kits, in particular to a female gestational hypertension gene noninvasive detection kit which comprises a kit body, a kit cover, a high-elasticity fixing part, a lifting frame and the like, the rear side of the kit cover is rotationally connected with the top of the kit body, the high-elasticity fixing part is located in the kit body, and the lifting frame is located in the kit body. The high-elasticity fixing piece is provided with a plurality of reagent cavities used for storing reagent tubes, the lifting frame is located at the top of the high-elasticity fixing piece, and the high-elasticity fixing piece can be compressed when the lifting frame descends. The opening action of the box cover is converted into the descending motion of the lifting frame through the transmission assembly, then the high-elasticity fixing piece is compressed, space is created for taking out reagent tubes, the taking process is simplified, the operation efficiency is improved, meanwhile, through the combined design of a pressing plate, a telescopic sleeve and a first elastic piece, the operation efficiency is improved, and the labor intensity is reduced. The reagent tubes with various lengths can be adaptively fixed, and the stability of the reagent tubes in the storage process is ensured.

This invention relates to the field of medical testing, specifically to a set of biomarkers, reagent kits, and their applications for diagnosing hypertension in children. This invention involves collecting tongue / intestinal samples from obese children with hypertension, obese children, and healthy individuals, performing metagenomic sequencing, and statistically analyzing the sequencing data using bioinformatics to identify disease-related tongue / intestinal flora. By integrating tongue / intestinal flora with disease information, a combination of flora biomarkers is obtained. A binary classification prediction model constructed using this combination can maximally detect hypertension in obese children.

The invention discloses a perioperative period hypotension risk prediction and early warning method and system based on artificial intelligence, belongs to the crossing field of medical artificial intelligence and clinical anesthesia, and is suitable for painless gastrointestinal endoscope perioperative period management of elderly hypertensive patients. Preoperative-intraoperative full-process data is obtained through a multi-source data acquisition module, after feature engineering processing, a double-order AI architecture of a preoperative risk layering sub-model and an intraoperative dynamic prediction sub-model is input, a comprehensive risk value is output through dynamic weight fusion, and a three-level early warning mechanism and an evidence-based intervention closed loop are combined to obtain an early warning result. And hypotension pre-prediction and individualized intervention are realized. According to the method, the problems of monitoring lag, poor generalization and other pain points in the prior art are solved, accurate early warning can be carried out 5 minutes in advance, the haemodynamic management accuracy and anesthesia safety in the perioperative period are remarkably improved, and the occurrence rate of hypotension and related adverse events is reduced.

The embodiment of the invention aims to provide a method and equipment for providing personalized health management for a user based on a hypertension prevention and treatment knowledge graph, a computer program storage medium and a computer program product. The method comprises the following steps: acquiring multi-modal data for constructing a hypertension prevention and treatment knowledge graph, including medical data and medical big data, so as to construct a standardized causal triple knowledge unit; according to the causal triple knowledge unit of the medical data, constructing a basic structure of a hypertension prevention and treatment knowledge graph; according to a causal triple knowledge unit of the medical big data, constructing the hypertension prevention and treatment knowledge graph which can be dynamically evolved; collecting personalized health data of the current user; and obtaining a dynamic hypertension health management scheme for the current user. The invention constructs a hypertension prevention and treatment knowledge system which is dynamically updated, highly personalized, comprehensive in data fusion, intelligent and efficient.

The invention provides a prediction system and method for gestational hypertension risk, and belongs to the technical field of gynaecology and obstetrics. According to the system, a data list generation module is used for generating a pregnant woman personal data list; the scoring module is configured to be used for processing and analyzing a pregnant woman personal data list, matching and contrasting each item of data in the pregnant woman personal data list with items in a preset judgment list, identifying matched data, scoring according to a corresponding preset rating standard to obtain main element scores, and sending the main element scores to the pregnant woman personal data list; summarizing the main element scores corresponding to the data to obtain a total score result; and the judgment module is configured to compare the total scoring result with a preset threshold value and judge the risk level of the hypertension risk in the gestation period of the pregnant woman. According to the method, personalized comprehensive risk assessment can be provided, the limitation of a traditional method is overcome, a doctor can formulate corresponding prevention and intervention measures according to specific conditions, and therefore the intervention effectiveness is improved.

Technology is described for identifying hypertension in a person. The method can include identifying a first group of medical features for a person at a first time point and a second group of medical features for the person at a second time point. An additional operation may be determining a time difference interval between the first time point and the second time point. The first group of medical features may be processed using an initial Bayesian belief network. An initial hypertension classification may also be received from the initial Bayesian belief network. In a further operation, the second group of medical features may be processed with an additional Bayesian belief network, while using the initial hypertension classification and the time difference interval as inputs. A joint hypertension classification may be obtained from the additional Bayesian belief network.

The present disclosure provides a modified oligonucleotide sequence and its application. A series of siRNAs are designed based on the angiotensinogen (AGT) messenger ribonucleic acid (mRNA) sequence, and are alternately modified and modified using a specific set of modification templates. The results of cell and animal experiments show that some alternately modified and specifically template-modified oligonucleotide sequences can significantly inhibit the expression of the AGT gene, and can be used for developing drugs for treating related diseases such as hypertension.

The invention relates to the technical field of old-age service management, in particular to an integrated old-age service management system based on end-cloud collaboration, and aims to solve the problems that in the prior art, multi-source data of physical signs, medication and living habits cannot be integrated to predict the health change trend, abnormal fluctuation of four high cannot be perceived in advance, short-term risks cannot be pre-judged, and the service quality is poor. And a personalized intervention scheme cannot be formulated in combination with reinforcement learning. Multi-source data of physical signs, medication and living habits are integrated through the chronic disease management module, LSTM is used for predicting the health change trend, four-high abnormal fluctuation is perceived in advance, short-term risks are pre-judged, a personalized intervention scheme is formulated in combination with reinforcement learning, diet and exercise suggestions and medication reminding are covered, and the system has the advantages of being simple in structure and convenient to use. User compliance is improved by outputting custom prompts through natural languages, the system forms a complete closed loop, the system is suitable for long-term management of diabetes and hypertension diseases, the risk of acute events is reduced, and the self-management ability of patients is enhanced.

The invention discloses a traditional Chinese and western medicine fusion diagnosis and treatment method based on an intelligent large model, and relates to the field of artificial intelligence and medical health, and the method comprises the steps: collecting traditional Chinese medicine four diagnosis information and western medicine diagnosis data of a patient, carrying out the standardized preprocessing through a unified interface, and obtaining structured input data; a traditional Chinese and western medicine diagnosis fusion inference framework is constructed by using a large model, cross-modal alignment and fusion are performed on a traditional Chinese medicine syndrome differentiation typing result and a western medicine diagnosis conclusion to form unified semantic representation, a causal robust modeling mechanism is introduced, and a personalized prescription diagnosis and treatment scheme is generated based on the unified semantic representation and causal robust features in combination with individual features of a patient. The problems that in the prior art, traditional Chinese and western medicine data splitting, individuation is insufficient, and intelligence and interpretability are poor are solved, the limitation that in existing traditional Chinese and western medicine diagnosis and treatment, data splitting, individuation is insufficient and intelligence is insufficient is broken through, and the technical effects that effectiveness, robustness and interpretability of hypertension diagnosis and treatment are improved are achieved.

The invention relates to a method for predicting intraoperative hypertension, and belongs to the field of digital medical treatment. Comprising the following steps: preprocessing, standardizing and marking collected patient data to obtain first data; selecting characteristic variables from the first data, and selecting influence characteristics from the characteristic variables according to correlation coefficient calculation and expert judgment; establishing a sample set based on the influence characteristics, and training through the sample set to obtain a trained intraoperative hypertension prediction model; preprocessing and standardizing data of a patient to be tested to obtain second data, and inputting the second data into the trained intraoperative hypertension prediction model to realize prediction of intraoperative hypertension of the patient. According to the method, the influence factors of intraoperative hypertension are searched from a large amount of data, and the intraoperative hypertension prediction model is trained based on the log-likelihood function, so that the accuracy of intraoperative hypertension prediction is improved, and the problem that current intraoperative hypertension prediction depends on clinical experience of doctors is solved.

The invention relates to the technical field of image classification, in particular to a gestational hypertension traditional Chinese medicine tongue diagnosis image classification method based on transfer learning. Firstly, a tongue diagnosis image of a gestational hypertensive patient is obtained, a tongue body area is extracted, and an indentation degree value is calculated based on shape and pixel position features to reflect the shape of fat tongue with indentation; further extracting a tongue middle area by considering that physiological water retention during pregnancy may cause tooth marks, determining a reflective connected domain by analyzing pixel reflective characteristics before and after filtering, and extracting shape characteristics of the reflective connected domain to obtain a dispersion degree value and characterize a greasy moss degree; the tongue diagnosis image purity is obtained by combining the color fluctuation and gray scale confusion conditions of the tongue middle area and integrating the indentation degree value and the dispersion degree value, so that the greasy coating state and the spleen deficiency and liver-yang hyperactivity conditions are reflected; and finally, training a neural network by using the purity of the tongue diagnosis image and the original visual features, classifying the tongue diagnosis image, obtaining a more accurate classification result, and assisting a doctor in performing accurate judgment.

The invention discloses a myocardial ischemia reperfusion injury animal model construction method and application thereof in the technical field of model animal preparation. The method comprises the steps of hypertension and hyperlipidemia pretreatment, standardized ischemia-reperfusion operation, immune microenvironment regulation and control and model evaluation and verification. According to the invention, model construction is carried out on an integrated model operation table, so that a standardized ischemia-reperfusion process is realized, reproducibility of a myocardial injury degree and an immune cell infiltration rule of the model is realized, and suitability of the model and nano-drug research is enhanced; and a reliable tool is provided for research and development of targeted drugs such as immune cell membrane coated nanoparticles.

The invention relates to the technical field of intelligent monitoring medical treatment of senile chronic diseases, and discloses a hypertensive brain injury early-stage monitoring and evaluation system and method based on multi-mode MRI data, and the system comprises a data collection module, a data preprocessing module, a virtual elastography analysis module, a microcirculation analysis module, a feature extraction and prediction model module, and a data visualization and report module. The method further comprises the steps of multi-modal MRI data collection, data processing, virtual elastic tensor calculation, lymphatic-like system function analysis, image feature extraction, prediction model construction, quantitative report generation and personalized suggestion providing. According to the method, virtual elastography analysis and microcirculation analysis technologies are combined, multi-dimensional data such as cerebrovascular elasticity modulus, blood flow velocity and lymphatic-like system function indexes are integrated, more comprehensive hypertension cerebrovascular injury assessment is provided, and in addition, the accuracy of hypertension cerebrovascular injury assessment is improved by combining a machine learning algorithm and radiomics characteristics. And a high-precision cerebrovascular injury prediction model is constructed.

The present invention concerns selective renal denervation treatment of drug resistant hypertensive patients by correlating the patients' genetic panel by categorization and hierarchy according to patients' genetic variants within the functional genes for heart activity, for the renin-angiotensin aldosterone system, and for renal activity.

This invention provides a method for hypertension risk assessment, relating to the field of epigenetic detection technology. It includes: performing event alignment and residual modeling on a qualified signal set to establish a base probability at the locus level and forming baseline features through neighborhood consistency screening; constructing a tunneling sensitization model and contextual attention, fusing discriminative and generative evidence to obtain enhanced features; quantifying IGF2BP3 and aligning and fusing it with the enhanced features; constructing an IGF2BP3-mediated metabolic network based on this, performing time-series modeling and stability assessment, and extracting final-state features; fusing the final-state risk vector with multi-gene scores to complete adaptive grading and compliant report generation. This method is robust, interpretable, and easy to deploy.

The invention discloses a mobile chronic health management system based on a large language model, and relates to the technical field of medical information, and the application comprises six main modules: a user interface module which is developed by adopting a Flutter front-end technology, allows a patient to input hypertension, diabetes and health data related to movement and sleep, checks a health data chart, and sends the health data to a central processing module; health questions and answers are carried out through a large language model; the logic control module is developed on the basis of a SpringBoot framework and is responsible for processing business logic and data interaction, providing a RESTfulAPI interface, managing addition, deletion, modification and check of health data, processing a data analysis request and calling a large language model; the database module is used for storing and managing system data by adopting a MySQL relational database; the big language model module is used for providing a health question and answer function based on the basic information and health data of the patient by utilizing a deep learning framework and a pre-trained big language model, and providing suggestions in the aspect of diet; the push reminding module is used for pushing notices through the system and reminding the patient to take medicine on time and perform physical examination; and the electronic case module allows the patient to edit and upload the personal medical information, and manages the personal medical information in a centralized manner. And intelligent management of chronic disease patients is realized.

The invention discloses an application of a small molecular compound SR9009 in preparation of antihypertensive drugs. The SR9009 is used for treating three common hypertension rodent animal models, a better antihypertensive effect is shown, the antihypertensive effect is possibly related to increase of urine sodium excretion and reduction of kidney epithelium sodium channel protein expression, possibility is provided for application of the SR9009 in prevention and treatment of hypertension diseases, and the SR9009 has a wide application prospect.

The invention discloses a primary hypertension risk assessment method based on infrared thermal imaging. The method comprises the following steps: (1) respectively taking two-hand infrared thermograms of a healthy subject, a hypertension patient and a hypertension patient before and after cold stimulation by adopting a medical infrared thermal imager; (2) analyzing hand infrared thermograms before and after cold stimulation of a healthy subject, a hypertensive patient and a hypertensive patient so as to reflect vascular reactivity and blood perfusion states of hands of the healthy subject, the hypertensive patient and the hypertensive patient; and (3) taking hand infrared thermograms of the to-be-tested subject before and after cold stimulation by adopting a medical infrared thermal imager, and obtaining a judgment result according to the vascular reactivity and blood perfusion state of the hand. According to the invention, a medical infrared thermal imager is utilized to shoot infrared thermograms of hands of a subject before and after cold stimulation, so that vascular reactivity and blood perfusion states are visually reflected in a non-contact, real-time and visualized manner, and finally, the purpose of evaluating the risk of primary hypertension is achieved.

The invention relates to a traditional Chinese medicine composition for treating hypertension as well as a preparation method and application thereof. The traditional Chinese medicine composition is prepared from the following components in parts by weight: 180 to 240 parts of radix astragali seu hedysari, 180 to 240 parts of fructus lycii, 180 to 240 parts of herba portulacae, 180 to 240 parts of spica prunellae, 25 to 45 parts of frankincense, 95 to 115 parts of radix salviae miltiorrhizae, 180 to 240 parts of fructus hordei germinatus and 95 to 115 parts of fructus cannabis. The traditional Chinese medicine composition disclosed by the invention shows a remarkable effect of treating hypertension, is stable and safe in medicine effect, and has good market application value and development prospect.

The application discloses a prognosis risk prediction model construction system and method based on chronic disease real world data, comprising a multi-source real world data acquisition and access module, a data standardization and quality control module, a multi-dimensional feature engineering and screening module, a comorbidity feature fusion and data set construction module, a prognosis risk prediction model training and optimization module, a model multi-dimensional verification and evaluation module, a model deployment and risk stratification output module; a special multi-source real world data acquisition and quality control system for chronic liver disease, diabetes and hypertension is constructed, data standardization processing is realized in combination with a chronic disease clinical diagnosis and treatment guideline, through multi-dimensional missing value, abnormal value processing and data deduplication integration, the quality and availability of the real world data are effectively improved, the core problem of disorderly and low-quality real world data in the prior art is solved, and a high-quality data source basis is provided for model construction.

The present disclosure provides a modified oligonucleotide sequence and use thereof. A series of siRNAs were designed based on the angiotensinogen (AGT) messenger ribonucleic acid (mRNA) sequence, which were alternately modified or modified using a specific set of modification templates. The results from cell and animal experiments demonstrated that some oligonucleotide sequences with alternating modifications and specific template modifications can significantly inhibit AGT gene expression and may be used for the development of medicaments for treating hypertension and other related diseases.

Embodiments of the present disclosure include a system, including an AI application, that determines updates prescriptions for a patient. Based on information about the patient's condition, an expert system uses pharmaceutical-specific models to predict the patient's responses to pharmaceuticals and / or potential dosages thereof. The system determines priority scores of classes of pharmaceuticals and, based on the priority scores, determines and stores an updated prescription.

The invention discloses a coronary artery CT imaging reexamination time window prediction method fusing multi-source information, and the method comprises the steps: collecting the multi-dimensional data of a patient, confirming an imaging index based on the multi-dimensional data, arranging baseline clinical information and the drug use condition of the patient based on the multi-dimensional data, concluding the CCTA reexamination time of the patient with coronary heart disease, and carrying out the prediction of the CCTA reexamination time of the patient with coronary heart disease. Constructing a multi-dimensional data set, preprocessing the data set, and performing assignment quantification on risk factors; a LightGBM sub-model is constructed through the processed data, the accuracy and generalization ability of a final prediction result are improved by adopting a Stacking method, and a model-independent local interpretable technology LIME is introduced to reduce a loss function; according to the method, the problem that the optimal CCTA review time window is difficult to accurately predict due to the fact that only traditional factors such as hypertension and diabetes are included in an existing evaluation method, and imaging information capable of directly quantifying and representing individualized plaque features, rich clinical information in electronic medical records and interaction among multi-source information are ignored is solved.

A laser irradiation system is disclosed. The system comprises a mobile application program executed in a mobile terminal of a user; a management server that determines whether the user is a hypertensive patient by receiving and analyzing the face image of the user from the mobile application; one or more laser radiators in which a plurality of light-emitting elements for radiating laser light to different parts of the body of a user in a lying position are arranged; and a controller that controls the laser irradiator. Further, the controller includes: a communication unit for performing close-range data communication with the mobile application; the information storage part stores meridian point information including acupuncture points for hypertension; and a control unit that, when data indicating that the user is a hypertensive patient is received from the mobile application via the short-range communication unit, drives and controls the light-emitting elements corresponding to the acupoints for hypertension stored in the information storage unit so as to irradiate the corresponding acupoints with laser light.