192 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 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 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.

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 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 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.

This invention discloses a radioactive molecular probe for targeting CSPG4 / NG2, its preparation method, and its application. The radioactive molecular probe comprises the structure shown in Formula I or Formula II. The technical solution of this invention uses a radioactive molecular probe to specifically recognize CSPG4 / NG2 in vivo through the target polypeptide portion, thereby achieving specific nuclear medicine positron emission tomography (PET) or single-photon emission computed tomography (SPECT) imaging diagnosis of CSPG4 / NG2 positive tumors or CSPG4 / NG2 positive lesions, such as autoimmune diseases and cardiovascular and cerebrovascular diseases, thereby realizing early diagnosis and efficacy evaluation of malignant tumors.

The invention relates to the technical field of cerebrovascular disease thrombectomy, and discloses an auxiliary device for cerebrovascular disease thrombectomy, which comprises two sliding joint mechanisms and a catheter limiting mechanism. According to the auxiliary device for the thrombectomy operation of the cerebrovascular disease, by means of the relative mobility of the X axis, the Y axis and the Z axis, the catheter positioning capacity at any space position can be achieved, the application range of the device is widened, the shaft body design is adopted, the occupation degree of the operation space can be reduced, and in addition, due to the fact that the auxiliary device is placed on the ground and has the braking capacity at the joints, the operation efficiency is improved. And the working stability is relatively high.

The invention provides a cerebrovascular disease diagnosis support method and system based on multi-modal image fusion, and belongs to the field of image processing, and the method comprises the steps: obtaining an MRA image and an MRI image of a patient, and obtaining a local region and blood vessel pixel points in the images; obtaining a plurality of filtering kernels of each local area by combining the gray distribution of the pixel points in the MRA image and the gray levels of the pixel points at the same positions in the two images; and obtaining the optimal filtering kernel of each local region according to the gray scale change of the pixel points before and after filtering of each local region by using each filtering kernel and the change of the gradient direction of the pixel points before and after matrix enhancement of the filtered region. The invention aims to solve the problem that the denoising effect is not ideal when all areas in an image are filtered and denoised through a filtering core of one scale due to non-uniformity of cerebral blood vessel distribution when the MRA image of the brain of a patient is filtered and denoised.

Embodiments of the present application disclose a cerebrovascular disease risk prediction method and device based on a distributed biological sample library. The embodiments of the present application can determine at least one target prediction end matched with a clinical feature vector from a plurality of candidate prediction ends based on a first collaborative prediction request sent by a prediction request end and local sample data features of the plurality of candidate prediction ends, send a second collaborative prediction request to each target prediction end, receive a second initial cerebrovascular disease risk probability and a corresponding second prediction confidence returned by each target prediction end, obtain a comprehensive prediction confidence by weighted fusion of a first prediction confidence and each second prediction confidence, and obtain a target cerebrovascular disease risk probability by weighted fusion of a first initial cerebrovascular disease risk probability and each second initial cerebrovascular disease risk probability, and send the target cerebrovascular disease risk probability and the corresponding comprehensive prediction confidence to the prediction request end. Thus, the embodiments of the present application improve the accuracy and reliability of cerebrovascular disease risk prediction.

The present invention relates to a protein degradation agent, a preparation method therefor, and a use thereof. The protein degradation can degrade various proteins including c-Myc protein, and therefore can be used for prevention and treatment of diseases related to disorders of various proteins including c-Myc protein, such as cancer; cardiovascular and cerebrovascular diseases, and viral infection-related diseases.

A cerebrovascular disease learning apparatus may be provided. The cerebrovascular disease learning apparatus may include a maximum intensity projection magnetic resonance angiography (MIP MRA) configuration unit configured to receive 3D time-of-flight magnetic resonance angiography (3D TOF MRA) and to construct MIP MRA including a plurality of image frames, a space characteristic learning unit configured to construct a space characteristic learning model, a frame characteristic learning unit configured to receive the space characteristics and to construct a frame characteristic learning model based on a recurrent neural network (RNN) learning method, and a lesion characteristic learning unit configured to receive the frame characteristics and to construct a lesion characteristic learning model based on the CNN learning method.

The application provides an application of scEMC10 in treatment and diagnosis of brain vascular endothelial cell aging, and relates to the technical field of biomedicine. The inventor finds that scEMC10 deficiency leads to brain microvascular endothelial cell aging; brain microvascular endothelial cells treated by scEMC10 can down-regulate beta-galactosidase, SASP and classic aging markers related to aging; after old mice and 5XFAD model mice of Alzheimer's disease are supplemented with scEmc10, the movement coordination ability and spatial cognitive ability of the mice can be obviously improved, and the relative content of the Parkinson's disease marker, phosphorylated alpha-synuclein, of the old mice can be obviously reduced, and the content of the tyrosine hydroxylase phosphorylation activity form can be increased. Therefore, scEMC10 can be used for treatment of brain microvascular endothelial cell aging, improvement of Alzheimer's disease and Parkinson's disease, and detection of brain microvascular endothelial cell aging as a marker.

The invention discloses a cerebrovascular disease risk prediction method, and particularly relates to the field of disease risk prediction, and the method comprises the following steps: S1, collecting basic clinical data, dynamic physiological parameter data and image feature data of a target object, and constructing a data set; s2, performing feature extraction on the basic clinical data, the dynamic physiological parameter data and the image feature data, and fusing the extracted features to obtain a fused feature set; s3, constructing a fusion prediction model through the fusion feature set; and S4, inputting the data set into the fusion prediction model, and outputting a risk prediction result. According to the method, the information short board of a single data type is made up, different types of data are converted into a unified computable form through standardized quantitative processing, core information with risk indication significance is effectively screened out in combination with abnormal data proportion analysis and dynamic fluctuation intensity evaluation, and the recognition capability of early potential risks of diseases is remarkably improved.

The invention provides a siRNA duplex for targeted regulation and control of LPA gene expression and application of the siRNA duplex in prevention and treatment of cardiovascular and cerebrovascular related diseases. The present disclosure also relates to corresponding conjugates and pharmaceutical compositions. Cell and animal experiment results show that the oligonucleotide duplex can significantly inhibit the expression of the LPA gene, and can be used for preparing drugs for preventing or treating atherosclerosis and other related diseases.