250 results about "Brain vessel" patented technology

The invention relates to the technical field of medical treatment, in particular to an intracranial aneurysm rupture risk assessment and management system based on an internet hospital, which comprises a patient end module, a patient end module, a management end module and a management end module, and the patient end module uploads medical history data and performs automatic filing and labeling processing on basic health data through a system standardization questionnaire and a multi-modal data acquisition mechanism; according to the method, the consistency and comparability of the health data are realized through vectorization coding and standardization processing; a blind deconvolution technology is adopted to improve the definition of a cerebrovascular image, and risk assessment is optimized in combination with the image and clinical features; privacy is protected through a self-adaptive watermarking technology, and data security and compliance are ensured in combination with double encryption and de-identification processing; the system timely identifies risks and pushes personalized health intervention through dynamic monitoring and intelligent early warning, and the accuracy and initiative of chronic disease management are improved. In addition, the block chain technology ensures data traceability and tampering prevention, and the doctor-patient trust is enhanced.

The invention relates to lauroyl cilostazol as well as a preparation method and application thereof. Wherein the lauroyl cilostazol is sterile, and preferably, the lauroyl cilostazol is a crystal. The invention further provides application of the lauroyl cilostazol in preparing medicines for treating cerebral infarction, cerebrovascular diseases, atherosclerosis, diabetic complications, peripheral vascular diseases, Reynolds diseases, intermittent claudication, ischemic heart diseases and acute coronary syndromes. The lauroyl cilostazol has the remarkable long-acting characteristic.

The invention discloses a cerebral apoplexy high risk group positioning evaluation system based on multi-modal data, and relates to the technical field of medical information science, the cerebral apoplexy high risk group positioning evaluation system comprises a cerebral apoplexy prevention and control management platform, and the cerebral apoplexy prevention and control management platform is in communication connection with the following modules: a multi-modal data acquisition and integration module, the multi-modal data collection module is used for collecting multi-modal data related to cerebral apoplexy from multiple channels and carrying out preprocessing operation on the collected multi-modal data. By integrating clinical data, image data, omics data and terminal health data, multi-dimensional information related to the cerebral apoplexy can be comprehensively captured, particularly, cerebral vessel digital twin is utilized to simulate hemodynamic characteristics, a plurality of data sources are fused in combination with a graph neural network, high-risk groups can be recognized more accurately, and the accuracy of cerebral apoplexy recognition is improved. The accuracy and reliability of risk prediction are remarkably improved, the problem of missing detection caused by dependence on a single data source in a traditional method is solved, and more powerful support is provided for early intervention.

The present invention relates to a free base crystal form of a nitrogen-containing heterocyclic derivative, an acid salt and a crystal form thereof, a preparation method therefor, and a use thereof. In particular, the present invention relates to a free base crystal form of a compound represented by a general formula, an acid salt and a crystal form thereof, a preparation method therefor, a pharmaceutical composition containing a therapeutically effective amount of the salt or crystal form, and a use thereof as an inhibitor in the treatment of diseases such as cardiovascular disease and cerebrovascular disease.

The invention relates to the technical field of medical artificial intelligence, in particular to a vascular embolism risk prediction method based on big data analysis, and the method comprises the steps: collecting a pulse pressure fluctuation rate, a microcirculation resistance index and a platelet adhesion gradient through a multi-source sensor, and extracting dynamic physiological parameter time sequence features; constructing a hemodynamic finite element model based on CTA and VFI image data, and obtaining a vascular mechanical feature vector; deep coupling of the pulse pressure spectrum and the circumferential stress is achieved through dynamic time warping and convolution mapping, and a multi-modal risk feature set is generated; and performing cross-modal coding by using the double-branch graph neural network, and outputting an acute embolism probability and a three-dimensional risk thermodynamic diagram. According to the method, physiological, image and mechanical multi-dimensional information is fused, and the method has the advantages of being high in real-time performance, accurate in positioning and good in interpretability and is suitable for risk prediction and auxiliary diagnosis of clinical cardiovascular and cerebrovascular events.

The invention relates to the technical field of monitoring for cerebrovascular disease rehabilitation teaching, and discloses a monitoring system for cerebrovascular disease rehabilitation teaching based on an AI technology. The system comprises an acquisition module, an extraction module, a frame module, an organization module, an analysis module and a rendering module, and sequentially realizes multi-modal teaching data acquisition, knowledge extraction, AI model training, teaching content organization, learner action evaluation and feedback rendering, and constructs an intelligent rehabilitation teaching display interface. According to the application, high-quality acquisition and fusion modeling of multi-modal data in cerebrovascular disease rehabilitation teaching are realized, and an AI teaching system with knowledge-driven and intelligent feedback capabilities is constructed, so that the individuation, systematicness and interactivity levels of rehabilitation action teaching are improved.

The present invention provides an isolated Akkermansia muciniphila strain, composition comprising the same, and use thereof, which can be used for treating, preventing, or alleviating obesity, metabolic disorders induced by obesity, diabetes, inflammation, liver and kidney diseases, liver diseases, cardiovascular and cerebrovascular diseases, brain aging, tumors, etc. Additionally, it can be used for preventing and treating metabolic disorders after discontinuation of GLP-1 receptor agonist drugs, preventing weight rebound and blood glucose rebound, and maintaining glucose homeostasis.

The present disclosure proposes a method for monitoring simultaneously vascular activity in at least one region of a brain, of a human or animal, and the temporal evolution of physiological parameters, the method including generating a sequence of Doppler or Ultrasound Localization Microscopy "ULM" images of said brain with an ultrasound probe and simultaneously computing physiological information based on a temporal series of brain tissue motion data in a selected region of interest of the brain.

The invention discloses a cerebrovascular disease health monitoring method based on an intelligent agent. The method comprises the following steps: step 1, acquiring multi-modal data in real time and preprocessing the multi-modal data; 2, converting the preprocessed multi-modal data into structured health status characterization, and identifying potential cerebrovascular risks; 3, analyzing through a cerebral apoplexy AI model, and outputting a risk level; 4, performing personalized early warning strategy planning based on the risk level; 5, converting an instruction of personalized early warning strategy planning into a cross-platform executable action; and 6, aggregating the desensitization data of the global cerebral apoplexy AI model at the cloud through federal learning, and updating the clinical knowledge graph rule base. According to the method, the health state of the patient is monitored by fusing the multi-modal data, the cerebral apoplexy AI model and the clinical mapping knowledge domain, patients with high-risk and medium-risk cerebrovascular diseases are screened out in time, and medical response is provided in time.

The invention relates to the technical field of cardiovascular system disease diagnosis, in particular to a cardiovascular disease onset risk prediction method and system. By combining multiple groups of indexes and image group feature data, early-stage evaluation can be effectively carried out on the cardiovascular disease, score data reflecting the cardiovascular disease can be obtained, and the incidence probability and incidence degree of the cardiovascular disease can be more intuitively determined through the score data. Therefore, the overall automatic prediction of the cardiovascular disease is realized.

The present invention relates to a solid nutraceutical composition for the prevention and treatment of cognitive disorders, consisting of an emulsion and a mixture of seed and oil, all of which are naturally derived. The emulsion contains plukenetia volubilis oil; an extract of plant origin, such as turmeric, pepper or cocoa; an emulsifier selected from lecithin, saponaria or maguey extract, or egg white; the sweetening agent is selected from fructo-oligosaccharide, stevia rebaudiana or maguey extract, Italian bee honey and cane sugar; and air is contained. Seeds and oil include pumpkin seeds and plukenetia volubilis oil. Other ingredients selected from cocoa powder, coconut oil, fruit or seed mass, natural juice and protein are also added. Thus, the nutraceutical comprises 3 to 5 sources of fatty acids, phytosterols and triacylglycerol, 2 to 8 sources of antioxidants, up to 3 sources of hypoglycemic agents, and up to 4 sources of anti-cholesterol and anti-inflammatory compounds. In addition, the nutritional health-care product also contains proteins, vitamins, macroelements, microelements and substances for promoting chewing and swallowing of subjects and patients suffering from cognitive impairment. The nutritional health-care product is suitable for preventing and treating Alzheimer's disease; mental, behavioral and developmental disorders, including depression; neurological, digestive, immune, endocrine and circulatory disorders; cardiovascular, cerebrovascular, infectious, parasitic, neoplastic and blood diseases; fatigue, fatigue and malnutrition.

The invention belongs to the technical field of medicines, and particularly relates to application of indole-3-lactic acid in preparation of medicines for treating diabetes and complications. A db / db mouse is utilized to simulate the pathological process of human diabetes, the db / db mouse is orally administered with indole-3-lactic acid, and after the db / db mouse orally administered with indole-3-lactic acid, the blood glucose and blood fat of the diabetic mouse can be reduced, the cardiac function impairment of the diabetic mouse is improved, and the brain cognitive dysfunction of the diabetic mouse is improved. It is proved that the indole-3-lactic acid has a treatment effect on diabetes and cardiovascular and cerebrovascular complications thereof.

The invention belongs to the technical field of medical image processing and neural image analysis, and particularly discloses a cerebral apoplexy prognosis prediction method which comprises the following steps: step 1, performing whole cerebral vessel segmentation and morphological feature extraction on a CTA image to obtain 40 blood vessel morphological features; 2, extracting high-throughput omics characteristics from an infarction core and a half-dark band region in the DWI image, and obtaining 1026 image omics characteristics; 3, screening high-resolution features based on minimum absolute contraction and a selection operator, establishing a support vector machine classification model, and predicting a prognosis classification result of a three-month improved Rankin scale of the stroke patient; the deep learning network is used for automatically segmenting the whole brain blood vessel, so that subjective difference of manual recognition is reduced; starting from pathophysiology of occurrence and development of cerebral apoplexy, vascular morphological characteristics and infarction region imageomics characteristics are comprehensively incorporated to carry out prognosis prediction on cerebral apoplexy.

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.

Use of an NLRP3 inhibitor for treating cerebrovascular diseases. Specifically, the present invention relates to use of a compound represented by formula (I) or a pharmaceutically acceptable salt thereof in the preparation of a drug for treating cerebrovascular diseases, wherein each substituent is as defined in the description.

Disclosed is a quinoline compound and a use thereof. A quinoline derivative of the present invention is a compound having phosphodiesterase 3A (PDE3A) inhibitory activity, has important potential therapeutic value, and is used in the treatment of cerebrovascular diseases or in dementia drugs.

The invention discloses a heart and cerebral vessel CTA accurate analysis method and system, and relates to the technical field of heart and cerebral vessels, and the method comprises the steps of 1, heart and cerebral vessel image collection, 2, heart and cerebral vessel image analysis, 3, heart and cerebral vessel image processing, and 4, heart and cerebral vessel result analysis. The quality coincidence index of each image of the cardiovascular and cerebrovascular CTA is analyzed, whether the image quality is abnormal or not is judged, the image quality is improved, the diagnosis accuracy is improved, misdiagnosis or missed diagnosis caused by the image quality problem is reduced, the reliability of the subsequent diagnosis result can be ensured, the working efficiency is improved, medical resources are more reasonably utilized, and the medical resource utilization rate is increased. The risk value of each blood vessel area of the cardiovascular and cerebrovascular CTA is assessed, and the diagnosis report is generated, so that a doctor can quantitatively assess the occurrence risk of cardiovascular and cerebrovascular diseases, and the doctor is helped to find potential health problems more timely and accurately.

The invention provides a traditional Chinese medicine composition for treating cerebrovascular diseases and a preparation method and application thereof, and belongs to the technical field of biological medicine. The traditional Chinese medicine composition is prepared from the following raw materials in parts by weight: 8 to 12 parts of rhizoma chuanxiong, 12 to 17 parts of radix paeoniae rubra, 13 to 18 parts of radix salviae miltiorrhizae, 8 to 12 parts of radix polygalae, 10 to 15 parts of rhizoma acori graminei, 27 to 32 parts of radix astragali seu hedysari, 0.3 to 0.7 part of borneol, 0.1 to 0.2 part of musk, 12 to 18 parts of radix angelicae sinensis, 6 to 12 parts of flos carthami, 7 to 12 parts of semen persicae and 5 to 7 parts of radix glycyrrhizae preparata. The traditional Chinese medicine composition disclosed by the invention has the curative effects of tonifying qi and activating blood, dispersing blood stasis and dredging collaterals, and restoring consciousness and inducing resuscitation. The traditional Chinese medicine composition can be combined with a leg electrical stimulation system to efficiently treat cerebral apoplexy hemiplegia and effectively treat vascular dementia, and has an obvious treatment effect on cerebrovascular diseases. The preparation method of the traditional Chinese medicine composition is simple, convenient and rapid, and is suitable for industrial production.

The invention relates to a medical data analysis method and device based on artificial intelligence, equipment and a medium. The method comprises the following steps: acquiring medical data of a user; the medical data comprises blood detection data, medical image index data and basic data, and the medical data is provided with a sampling time label; extracting a change trend of the medical data to obtain a comprehensive feature vector; the comprehensive feature vector at least comprises a blood detection change vector and a medical image index change vector; calculating weighted weights of the blood detection change vector and the medical image index change vector in the comprehensive feature vector, and adjusting the comprehensive feature vector based on the weighted weights to obtain a fused feature vector; and predicting a disease type and a disease risk probability of the user based on the fusion feature vector, and generating a medical report of the user based on the disease type and the risk probability. By adopting the method, the accuracy and timeliness of cardiovascular and cerebrovascular medical data analysis can be improved.

The invention discloses a DL-based multi-time-sequence brain NCCT image processing method and device, a medium and a program product, and the method comprises the steps: carrying out the image enhancement through employing CDGM, starting a deformation registration process based on an ANTs frame and fusing a cost function mask, and completing the space alignment of a multi-time-sequence brain NCCT image; according to the improved 3D Transform-UNet, an encoder of a SwinUnetR network is used, a self-attention mechanism of a local window and a self-attention mechanism of a shift window are embedded, a space prior probability graph is used for space constraint, and deep space feature extraction is completed; on the basis of a Transform encoder and a multi-head self-attention mechanism, aggregation of time sequence features is completed; a downstream task is used as a constraint, and a combined multi-task optimization strategy is adopted to obtain a dynamic feature embedding vector representing the dynamic evolution rule of the lesion. According to the method, the technical bottlenecks of a traditional method in the three aspects of space-time registration precision, feature extraction and clinical interpretability are broken through, and reliable technical support is provided for accurate diagnosis and treatment of cerebrovascular diseases.

The present invention relates to a novel route for preparing oxopyridine compounds shown in formula (I) and their key intermediates. The novel route provided by the present invention can greatly reduce the generation of isomeric impurities, improve the chiral selectivity of the reaction and the N / O-alkylation selectivity, increase the yield, eliminate the need for further purification of the crude product, reduce the cost, shorten the production cycle, save energy and protect the environment, and is suitable for use in the preparation of drugs for treating and / or preventing diseases related to the FXIa receptor, especially providing a new idea for the preparation of drugs for treating and / or preventing cerebrovascular arterial diseases and / or peripheral arterial diseases.

The present invention are co-crystals of Uric Acid with increased solubility with respect to crystals of Uric Acid, suitable for the pharmaceutical use. The invention comprises co-crystals with L-lysine, L-arginine, ethylene diamine, and tromethamine as co-formers, pharmaceutical compositions thereof and their therapeutical use in the prevention or treatment of cerebrovascular diseases.

The present invention belongs to the field of drug synthesis, and specifically relates to a heterocyclic derivative inhibitor, and the preparation thereof and the use thereof. Disclosed in the present invention is a compound having a structure as represented by formula I, or an isomer or pharmaceutically acceptable salt thereof. The compound of formula I provided by the present invention has strong PCSK9 inhibitory activity, and can be used for treating and / or preventing cardiovascular and cerebrovascular diseases.

The present invention belongs to the fields of medicine, health care and food, and specifically relates to use of a composition of alcohol and a cooling agent in regulating sexual functions, protecting cardiovascular and cerebrovascular systems, promoting regeneration of liver cells, preventing and / or treating tumors, and improving immunity and sleep quality. The technical problem to be resolved by the present invention is to provide the use of a composition of alcohol and a cooling agent in regulating sexual functions, protecting cardiovascular and cerebrovascular systems, promoting regeneration of liver cells, preventing and / or treating tumors, and improving immunity and sleep quality. The composition of the present invention includes the alcohol and the cooling agent. Further, the composition includes an organic acid. The alcohol in the composition is 1%vol-99%vol, and the cooling agent therein is 0.05ppm-500ppm. The composition provided according to the present invention can play the role of regulating sexual functions, protecting cardiovascular and cerebrovascular systems, promoting regeneration of liver cells, preventing and / or treating tumors, and improving immunity and sleep quality in a short period.

This invention relates to inhibitors of nitrogen-containing heterocyclic derivatives, their preparation methods, and applications. In particular, this invention relates to compounds of general formula (I), their preparation methods, pharmaceutical compositions containing such compounds, and their use as inhibitors in the treatment of cardiovascular and cerebrovascular diseases, wherein the substituents in general formula (I) are the same as defined in the specification.

The first-aid device structurally comprises universal wheels, a damping device, a transfer device, a supporting plate, a bed body and a first-aid kit, when a patient lies on the bed body and is transferred to an operating room for operation first aid, an installation assembly is installed on the supporting plate in parallel, and the installation assembly and the supporting plate are connected together in a matched mode; the lead screw and the rocking wheel are welded together to be inserted between the mounting assembly and the moving assembly, the lead screw can parallelly penetrate and stretch into two fixing bases on the mounting assembly to move, the lead screw and the rocking wheel are matched to rotate clockwise, the moving assembly can move outwards from the mounting assembly, and otherwise, the lead screw and the rocking wheel are matched to rotate anticlockwise, so that the moving assembly moves outwards. And the moving assembly can move inwards from the mounting assembly, so that the patient is transferred more stably, and the patient can be conveniently transferred to a first-aid table.

The application discloses a portable detection kit for assisting in predicting a cerebral vascular risk, a blood sample is processed through a sample processing module and input corresponding test paper, a detection result of the test paper is collected by a biological sensing module, and the detection result is calibrated and temporarily stored through an electronic control module, so that a user can acquire the calibrated detection result through a target device in an NFC touch mode and automatically send the calibrated detection result to a cerebral vascular disease monitoring digital platform, cerebral vascular risk prediction is performed by the cerebral vascular disease monitoring digital platform, and the portable detection kit has the beneficial effects of high portability, simple operation and high detection result accuracy.

The invention provides an immersive medical image teaching system and method based on a virtual digital human, and the system comprises a case data module which is used for importing case data, and generating a case database; the virtual digital person generation module is used for generating a virtual digital person according to the case data; the 3D simulation endoscope imaging module is used for generating a 3D simulation endoscope image according to the case data; the interactive logic engine is used for forming a teaching process script according to teaching logic and driving the virtual digital human to carry out narrative guidance and operation simulation; the teaching evaluation module is used for recording the learning path of the learner and evaluating the learning effect of the learner according to the learning path; according to the method, immersive medical image teaching based on the virtual digital human is realized through the system; the medical image teaching effect and efficiency are remarkably improved, and the system is suitable for multiple sub-fields such as chest and abdomen, heart and cerebral vessels, orthopedics and the like.

This invention discloses a two-stage method for generating brain vascular images and labels. First, labeled and unlabeled brain vascular images are processed separately to obtain training set 1 and training set 2. Then, a two-stage generative adversarial network (GAN) model for brain vascular image-label generation is constructed and trained using training set 1 and training set 2. Finally, N-dimensional noise is input into the trained model to obtain a complete brain vascular image. This invention utilizes a two-stage GAN model with pseudo-labels and real data input to generate brain vascular images and labels respectively. The generated brain vascular images have clearer voxels around the blood vessels and stronger connectivity of the vascular labels. Data augmentation applied to segmentation tasks can improve the accuracy of brain vascular structures segmented from brain vascular images, facilitating subsequent pathological image diagnosis. Simultaneously, the use of pseudo-labels alleviates the shortage of labeled medical image data.