189 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 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.

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.

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 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 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 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.

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.

Provided is a method for treating a condition selected from the group consisting of pain, sleep disorder, cancer, Alzheimer's disease, neurodegenerative diseases, ulcer, hypertension, opioid- related adverse effects, inflammation, asthma, glaucoma, neurodevelopment diseases and combinations thereof in a subject in need thereof, the method comprising administering to the subject: a) a first active pharmaceutical ingredient (API) comprising at least one cannabinoid other than CBD and THC; and b) a second API, which is different from the first API.

The invention discloses a remote ischemia adaptive hypertension treatment and risk assessment system based on artificial intelligence. The system comprises a physiological signal acquisition module, a preprocessing module, an artery function assessment module, a heart rhythm analysis module, a molecular biology assessment module, a user state association module and an assessment module. The physiological signal acquisition module is responsible for executing standard distant ischemia adaptation training and acquiring original data including systolic pressure, diastolic pressure, heart rate and pulse waveform data of upper limbs on two sides in real time in the execution process; the preprocessing module can sequentially carry out band-pass filtering, waveform segmentation and feature extraction processing on original data, then feature values extracted from single waveforms and the waveforms are combined to form a data set, and the data set is output. According to the method, arteriosclerosis can be evaluated, subclavian artery stenosis can be judged, and the nitric oxide amount can be calculated synchronously, so that fusion of multiple physiological data can be ensured in an adaptive treatment process, and meanwhile, multi-data joint evaluation is realized in combination with artificial intelligence.

The utility model relates to the technical field of accurate medication devices, and discloses an accurate medication device for old-age hypertension complication, which comprises a storage box, a cover is hinged to the outer wall of the storage box, an observation hole is formed in the inner wall of the cover, a hanging rope is fixedly connected to the top of the storage box, and a ringing type alarm clock is fixedly connected to the inner wall of the hanging rope. The front face of the storage box is fixedly connected with a magnet. As long as the storage box is arranged beside the elderly patient, an alarm clock of daily medicine taking time is set in advance, then the elderly patient is reminded to take medicine through the ringing type alarm clock, the storage box is convenient to carry through the hanging rope, the burden of the elderly patient is reduced, meanwhile, the storage box is convenient to open in a magnetic attraction mode, and the storage box can be conveniently taken only by opening the cover. And then the cover drives the auxiliary magnet to be separated from the magnet, so that the cover is opened to facilitate use, the situation that the treatment course is prolonged due to the fact that the elderly patient forgets to take medicine is effectively prevented, and the treatment effect is improved.

The invention relates to the technical field of biological medicines, in particular to application of GPR146 serving as a target spot to preparation of drugs for preventing or treating hypertension-related diseases. The invention relates to application of GPR146 in treatment of hypertension, and provides close correlation between GPR146 in smooth muscle and hypertension for the first time by comprehensively applying methods such as transcriptome sequencing, functional experiments and animal models, and a specific regulation mechanism of GPR146 in occurrence and development of hypertension is deeply discussed, so that a new insight is provided for revealing pathogenesis of hypertension.

This invention discloses a method for analyzing hypertension risk factors, applied in the field of computer science. It addresses the problems of existing technologies in analyzing and screening important risk factors for hypertension, such as high requirements for data quality, large manual processing workload, and the inability of analysis results to meet the accuracy requirements of downstream prediction tasks, as well as low operability with high-dimensional data. This invention employs a two-stage approach to screen the set of risk factors causing hypertension. The first stage uses domain knowledge to stratify attributes, then uses mutual information calculation to determine the number of candidate features in each stratum, and then uses mRMR (modular risk factor analysis) to screen the candidate set of risk factors in each stratum. The second stage uses a search agent to search for the optimal set of risk factors in the candidate set. A perceptron is added to sense the quality of the solutions corresponding to the search agent, and a random mutation operator is added to the search agent to perform a secondary screening of features, obtaining the final set of risk factors.

The invention specifically discloses a medication safety assessment method and system for hypertensive patients, and the method comprises the following steps: extracting one-complaint five-history, medication records, inspection indexes and outcome data of the hypertensive patients from an electronic health record system (EHR), carrying out the preprocessing, extracting key entities, and carrying out the verification of the key entities; constructing a comprehensive data set of'co-disease-medication-examination-symptom 'of the patient, identifying a co-disease combination strongest associated with hypertension, and mining specific adverse reaction signals under the co-disease combination; key factors causing adverse reactions or unreasonable medication are attributed through a multi-factor conditional logic regression or decision tree model; and based on common disease combination and multi-factor logistic regression analysis of one complaint and five histories, performing pairing t inspection on laboratory indexes, and generating a medication safety report of the hypertension common disease patient. By adopting the technical scheme, through multi-dimensional data analysis, specific influence factors causing adverse drug reaction or unreasonable drug use are attributed, and accurate drug use safety guidance is provided for clinicians.

The application discloses application of Dingxuan Granules in preparation of medicines for treating early kidney damage caused by hypertension of the type of yin deficiency and yang hyperactivity, and the Dingxuan Granules are prepared from radix rehmanniae, lycium barbarum, gastrodia, uncaria, wine salvia miltiorrhiza, alisma, motherwort and achyranthes bidentata. The Dingxuan Granules have the effects of tonifying liver and kidney, calming liver wind and promoting water and descending qi, and are suitable for people with early kidney damage caused by hypertension.

This invention relates to the field of cardiovascular disease auxiliary diagnosis technology, specifically to a method and system for auxiliary diagnosis of high-altitude hypertension based on electrocardiogram (ECG). It uses 12-lead ECG images as input, constructs a multi-branch adaptive classification model that integrates regional priors, sequentially extracts shallow general features through a shared feature extraction module, combines independent feature branches from multiple leads with a paired spatial attention module to capture relative potential differences between leads, and a multi-path adaptive fusion module dynamically fuses differential features between high-altitude and plain areas using regional labels as gating signals. Finally, a hybrid classifier composed of capsule networks and DenseNet cascades the features to complete a four-class prediction: high-altitude hypertension, high-altitude normal, plain hypertension, and plain normal. This invention effectively overcomes the problem of cross-regional data domain shift, improves the ability to capture weak pathological features in ECG images, and has strong clinical transferability and robustness, making it suitable for auxiliary screening of hypertension across high-altitude and plain areas.