18982 results about "Disease" patented technology

The invention relates to the technical field of civil engineering tunnel structure safety monitoring and intelligent detection, in particular to a multi-modal fusion tunnel structure apparent disease identification and risk assessment system, which comprises an image acquisition module used for acquiring continuous images of the inner wall of a tunnel lining; a laser point cloud acquisition module; a structure sensor acquisition module; a data synchronization and preprocessing module; the multi-modal feature extraction module is used for performing depth feature extraction on the image, the point cloud and the sensor data; the heterogeneous feature fusion and disease identification module is used for fusing each modal feature and outputting a disease type identification result; and the risk assessment module is used for carrying out size estimation and parameterized expression on the identified diseases. The problems that in an existing tunnel inspection technology, the detection means is single, appearance and internal information cannot be considered, and the disease size is difficult to quantify automatically are solved.

The invention discloses an unmanned aerial vehicle laser and vision fusion inspection method and system for bridge bottom disease detection, and the method comprises the steps: carrying out the synchronous data collection through employing a calibrated laser radar, a camera and an IMU, and obtaining a three-dimensional laser point cloud and a two-dimensional visual image of the appearance of a bridge; sharpening the image containing the motion blur and completing brightness self-adaption of the image; stable feature points are extracted, multi-frame matching is carried out, the corresponding poses of the images are estimated, and bridge dense point cloud reconstruction is completed; performing geometric component segmentation on the point cloud to generate a geometric prior region; component segmentation is carried out on a support area in the image, and a continuous and accurate component segmentation result is obtained in combination with a geometric prior area; screening the image, calling a targeted disease detection model in a corresponding component area, and generating a segmentation mask for the disease; obtaining a real disease three-dimensional point cloud, and carrying out quantitative calculation on the physical size of the disease; and displaying the real disease three-dimensional point cloud data and the physical size of the disease. The method is high in efficiency and precision.

The present application provides a method for diagnosing and / or evaluating the presence or absence, severity or degree of the improvement of a retinal disease in a subject, which comprises determining and / or evaluating circulatory parameters, retinal function, retina morphology and / or visual relating quality of life (QOL).

Frog farming method and frog cage are provided. The method comprises: I, putting young frogs in the frog cage in spring; II, putting lure attracting mosquitoes into the frog cage into the frog cage in summer and autumn, thereafter the frogs feed on the mosquitoes; III, avoiding snakes entering the frog cage in the place where the snakes inhabit; IV, covering the frog cage with plastic film in winter, mounting an electric lamp in the frog cage, increasing the temperature of air in the frog cage to keep the frogs not hibernating and promote the frogs to grow; V, adding artificial lure if necessary. The frog cage includes a fixed frog cage and a vehicle-mounted frog cage, both including inner tiers, wherein a water basin, a terrace and a stairway communicating the upper and lower tiers are arranged on each tier, and the frog cage is covered with a mesh enclosure. The frog framing method and frog cage have the advantages that the frogs are farmed in multi-tier cages, lures are used outdoors to attract insects, pests are eliminated for crops, natural ecology is balanced, and food sources are also provided for human; cage framing of frogs is very low in cost; frogs farmed have high reproductive rate, high disease resistance and high feed conversion capacity.

The invention discloses an illness state tracking management system and method based on a lingual face diagnosis instrument, and belongs to the technical field of traditional Chinese medicine tongue diagnosis and modern information technology fusion. The system comprises a multi-modal data acquisition module, a data processing and analysis module and an augmented reality visualization module; according to the method, illness state tracking is achieved through the steps of multi-modal data acquisition, data preprocessing and feature fusion, personalized digital twinborn model establishment, augmented reality visualization presentation and the like, multi-dimensional data such as tongue picture macroscopic features and tongue surface microorganism distribution can be integrated, dynamic association between the data is revealed, the health state and the intervention effect are visually displayed, and the method is suitable for being popularized and applied. The method is suitable for the fields of traditional Chinese medicine health management and chronic disease monitoring.

The invention relates to the technical field of medical decision, and discloses a medical decision support system based on a knowledge graph, and the system comprises a knowledge graph construction module which constructs an initial knowledge graph based on a medical ontology library, and the knowledge graph comprises entities and association relationships of diseases, symptoms and drugs; the data acquisition module is used for acquiring data from an electronic medical record, wearable equipment, a medical literature library and a hospital information system and normalizing the data through a standardized protocol; the dynamic knowledge updating module is used for processing normalized data through an incremental graph neural network; a multi-source knowledge fusion module; a context awareness module; a dynamic deduction module; and a decision optimization closed loop module. And triggering a preset clinical rule in real time based on the pathological state of the patient, dynamically adjusting the intensity value of the related edge in the factor graph, and persistently storing the intensity value back to the knowledge graph, so that logic adaptation and individualized experience precipitation of general medical knowledge in a special pathological state are realized, and the individualized treatment accuracy is ensured.

The invention discloses a traditional Chinese medicine famous prescription and operation multi-agent collaborative consultation method and system. The system comprises a medical case knowledge base module, an expert knowledge base module, a medicine knowledge base module, a pre-differentiation module, a multi-agent diagnosis module and the like. The method comprises the following steps: constructing structured experience medical case data, an expert experience knowledge graph and a traditional Chinese medicine knowledge graph knowledge base, carrying out mixed retrieval to carry out pre-differentiation, calling multi-agent consultation according to preliminary disease differentiation and syndrome types, and obtaining an expert diagnosis scheme for risk verification and prescription adjustment optimization. According to the invention, a multi-agent collaborative diagnosis technology is utilized, and a multi-agent architecture for simulating real traditional Chinese medicine consultation is constructed. A plurality of expert agents perform independent diagnosis and complement each other, so that the limitation of a single agent is avoided, and comprehensive and accurate diagnosis is provided. And in combination with expert experience knowledge graph and big language model reasoning, the system can flexibly differentiate symptoms according to the symptoms of the patient, accurately judge disease types and syndrome types, and improve the differentiation accuracy.

The invention discloses a cold region tunnel freeze injury diagnosis, risk grading and control system and method, and relates to the technical field of tunnel engineering. The system comprises a basic data layer for storing disease, index and measure databases; the core analysis layer is used for diagnosing a frost heaving mechanism, identifying single-factor, double-factor and three-factor frost heaving types, calculating freezing depth and frost heaving force and analyzing sensitivity; the risk level evaluation layer is used for dividing a disease zone, a frost heaving level, a freezing injury risk and a freezing injury risk response level; and the intelligent decision-making layer constructs an intelligent comprehensive decision-making analysis platform to realize risk-measure accurate matching and closed-loop management and control. The method comprises the four steps of data acquisition and storage, frost heaving mechanism diagnosis and quantification, risk grade evaluation and intelligent decision measure matching, through multi-source data fusion, multi-factor coupling analysis and zoning and grading prevention and control, the whole-process accurate management and control of the cold region tunnel frost damage is realized, and the frost damage treatment efficiency and the tunnel operation safety are improved.

The invention discloses a bovine I-type alpha interferon-ferritin fusion protein, a mutant thereof, a preparation method and an application of the bovine I-type alpha interferon-ferritin fusion protein. The bovine I-type alpha interferon is fused with a ferritin subunit, and interferon molecules are highly repeatedly and orderly displayed on the surface of a ferritin nanocage by utilizing the self-assembly characteristic of ferritin, so that the expression level, the structural stability and the antiviral activity of the interferon are remarkably improved. The fusion protein is further subjected to single-site or multi-site rational design mutation, and a mutant with significantly improved antiviral activity and stability is obtained. According to the invention, a silkworm or insect cell eukaryotic expression system is adopted to express the fusion protein or the mutant thereof, and the expression system is safe to operate, simple and convenient in procedure, low in cost and extremely beneficial to large-scale industrial production; the prepared fusion protein or mutant nanoparticles have application prospects in preparation of drugs or reagents for preventing or treating bovine viral diseases.

A compound, as shown in Formula I, is a multi-heterocyclic compound. It has been verified that the compound provided by this invention integrates a novel compound targeting the calcitonin gene-related peptide (CGRP) based on ephedrine. Upon contact with the skin, due to photoactivated cell biological function regulation and the blocking effect of the multi-heterocyclic compound I structure on serotonin receptors, it achieves therapeutic effects on cutaneous vascular malformations and telangiectasia, improves the effectiveness of phototherapy in improving chronic cutaneous vascular diseases, and promotes skin wound healing.

The invention discloses a medical data structured extraction method based on machine learning, and the method comprises the following steps: carrying out the standardization processing of multi-source heterogeneous data in different medical scenes, constructing a time and condition two-dimensional filtering rule, and extracting preliminary data; and a modular index structure is formed according to medical process and technical attribute division. And generating analysis limiting conditions by fusing the medical knowledge graph and the knowledge base, guiding an analysis engine to perform semantic routing and reasoning, and outputting a structured result. Finally, disease identification and quality judgment are achieved, and structured information meeting or not meeting the standard is output. The method aims at efficiently extracting the structured information from various types of medical documents.

The invention discloses an acute pancreatitis complication assessment method based on artificial intelligence, and belongs to the technical field of medical information, and the method specifically comprises the steps: firstly, obtaining a clinical data set containing real-time clinical indexes and basic disease historical records; performing time sequence analysis on the historical records of the basic diseases, extracting long-term influence characteristics of the historical records of the basic diseases and generating basic disease influence factors; carrying out standardization processing on the real-time clinical indexes and the basic disease influence factors, and generating a comprehensive feature vector after calculating association weights among features; inputting the vector into a trained artificial intelligence evaluation model, and outputting a complication risk probability through layer-by-layer nonlinear transformation; and finally, mapping the risk probability value into a risk level, and integrating patient information to generate a structured risk assessment report. And an acute pancreatitis complication evaluation scheme integrating the acute stage index and the chronic basic disease influence is established.

The invention provides a medical agent middleware-based full-specialized collaborative diagnosis and treatment method and system, and relates to the technical field of medical agents, and the method comprises the steps: building a basic medical knowledge graph through reinforcement learning, converting expert diagnosis and treatment experience into diagnosis and treatment probability distribution through a personalized treatment decision model, and forming an enhanced medical knowledge graph; and calculating a matching probability with a disease based on the symptom feature vector of the patient to generate a preliminary diagnosis decision, and selecting and adjusting a treatment scheme through reinforcement learning. According to the invention, general and specialized collaborative diagnosis and treatment can be realized, and medical decision accuracy and diagnosis and treatment efficiency are improved.

The invention discloses a colorectal cancer drug relocation method based on multi-omics integration. The system comprises a multi-omics data acquisition and preprocessing module, a tumor microenvironment analysis module, a specific disease network construction module, a multi-dimensional drug relocation module and a result evaluation module. And the tumor microenvironment analysis module comprises cell heterogeneity identification, cell map construction, cell annotation and tumor cell subset annotation. The specific disease network construction module comprises tumor feature expression program extraction, expression program screening, meta-program construction, clinical related meta-program recognition and specific disease protein interaction network construction. And the multi-dimensional drug relocation module comprises a module for identifying diseases by using a random walk algorithm, carrying out drug screening based on disturbance data, carrying out drug screening based on network proximity and carrying out comprehensive drug relocation. From the perspective of single cell data, element programs related to colorectal cancer survival are excavated, corresponding modules are designed, and the efficiency and precision of colorectal cancer targeted drug screening are improved.

The invention discloses an underground engineering lining disease detection system based on point cloud, and belongs to the technical field of underground engineering detection. In order to solve the technical problems that an existing underground engineering lining disease detection method is low in detection precision, low in automation degree and the like, underground engineering point cloud data to be detected and corresponding position information are collected, and an improved PointNet + + model is adopted for disease recognition. According to the method, original three-dimensional coordinates of a point cloud are expanded into seven-dimensional point cloud data containing coordinates, normal vectors and reflection intensity, the normal vector standard deviation of points in a neighborhood of each candidate point is calculated to serve as local geometric complexity, a local geometric complexity index is fused into sampling distance measurement, then a multi-scale local neighborhood is constructed by combining sphere query, and therefore the multi-scale local neighborhood is obtained. And extracting geometric features, texture features and deformation features by using a PCA feature dimension reduction technology, carrying out feature fusion based on a normal vector weighting mechanism, finally obtaining disease type classification based on a network model, and calculating the size and position of the disease.

The invention relates to a tunnel three-dimensional disease intelligent identification system and method based on a large model, the system comprises a point cloud data acquisition module and a processor, and the processor comprises a data processing module, a three-dimensional tile optimization module and a disease identification module. The data processing module carries out standardization, noise reduction and registration processing on the received point cloud data; the three-dimensional tile optimization module constructs a multi-level tile pyramid structure based on the registered point cloud data, establishes a mapping relation between a space coordinate and a tile index, compresses tile data based on a curvature point cloud simplification algorithm and adjusts texture quality to form a three-dimensional tile image; calculating a comprehensive score of the tile quality to verify the quality of the three-dimensional tile image; a disease identification module extracts multi-modal fusion features of the preprocessed three-dimensional tile image and geometric features corresponding to disease types; fusing the multi-modal fusion feature and the geometric feature to obtain a joint fusion feature; performing field fine tuning on the joint fusion features; and obtaining a disease identification result.

The invention relates to the technical field of intelligent diagnosis and treatment, and discloses a remote intelligent disease diagnosis and treatment system and method based on a block chain. The method comprises the steps that multi-modal physiological data such as real-time vital signs, historical medical record texts and medical images of a patient are collected, an encrypted data packet is generated, distributed storage is conducted through a block chain node network, and a data hash value and a timestamp are generated; and calling an intelligent contract to extract cross-modal features, generating a standardized feature vector set containing a multi-feature association identifier, and constructing a diagnosis and treatment decision tree capable of dynamically adjusting branch paths according to the standardized feature vector set. Verifying decision validity through a consensus mechanism, and generating a treatment instruction sequence containing drug configuration, instrument operation and a follow-up visit period; and monitoring feedback data in real time and updating the feedback data to the block chain, triggering an intelligent contract to generate a correction scheme when the deviation exceeds a threshold value, and writing the difference data as a new transaction record into the block chain, thereby realizing multi-modal data security management and control and dynamic precise diagnosis and treatment.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an artificial intelligence medical diagnosis system based on multi-dimensional information fusion. Comprising the steps that a self-adaptive diagnosis path planning module judges whether a user request belongs to a preset non-diagnosis and treatment category or not, if yes, a quick response path is activated, and a standardized answer is retrieved and returned to a user; the preliminary diagnosis module generates a candidate disease hypothesis list, verifies the candidate disease hypothesis list and outputs a verified disease hypothesis list; the dynamic knowledge enhancement module generates missing knowledge according to the disease knowledge graph and the query verification disease hypothesis list and supplements the missing knowledge into the medical knowledge graph; a composite confidence evaluation module performs confidence evaluation on each hypothesis disease in the verification disease hypothesis list, and outputs a final disease confidence; the result integration module sorts the final disease confidence in a descending order and integrates the multi-dimensional information of each hypothetical disease to generate a structured differential diagnosis report; the system and the method can assist doctors in realizing high-accuracy, high-reliability and explainable intelligent medical diagnosis.

Pharmaceutical formulations of novel indole compounds and psilocybin analogs are manufactured, provided in novel oral, transdermal, and nasal pharmaceutical compositions for use to treat neurological, mood or abuse diseases and disorders.

The invention discloses an AI-driven disease diagnosis and curative effect monitoring analysis system, which comprises a data processing module used for collecting multi-source diagnosis and treatment data and constructing a multi-modal sample set; the diagnosis prediction module is used for generating a diagnosis label, a diagnosis confidence value and a prediction curative effect trend through a multi-task learning model; the curative effect comparison module is used for collecting actual curative effect data, constructing a curative effect observation sequence and generating a curative effect deviation sequence based on the curative effect observation sequence and the predicted curative effect trend; the credibility evaluation module is used for executing credibility review based on the curative effect deviation sequence and the diagnosis confidence value; and the path evolution module is used for recording continuous multi-round diagnosis correction results, generating a jump type diagnosis path and updating a diagnosis and treatment data chain. The dynamic closed-loop verification mechanism between the multi-mode diagnosis and treatment data and the predicted curative effect trend improves the accuracy of disease diagnosis, the reliability of curative effect prediction and the adaptability of the diagnosis and treatment process.

Pharmaceutical formulations of novel indole compounds and psilocybin analogs are manufactured, provided in novel oral, transdermal, and nasal pharmaceutical compositions for use to treat neurological, mood or abuse diseases and disorders.

The application discloses a compound and application thereof, and belongs to the technical field of biological pharmacy. The compound has a structure shown in formula (I), or a deuterium compound thereof, or a stereoisomer thereof, or a pharmaceutically acceptable salt thereof. The compound has good PDE3 and / or PDE4 inhibiting effect, and is of great significance to the preparation of a medicine for PDE3 and / or PDE4 related diseases.

The invention discloses a virulent bacteriophage vBValSR36H with a host being vibrio alginolyticus and application of the virulent bacteriophage vBValSR36H, and relates to the technical field of microbial control. The invention provides a bacteriophage capable of efficiently cracking Vibrio alginolyticus ATCC 17749T, the bacteriophage is named as vBValSR36H, the preservation number is 66248-B1, and the preservation address is Institute of Microbiology, Academy of Sciences in Guangdong Province. The vibrio alginolyticus bacteriophage vBValSR36H provided by the invention has good environmental stability and certain bactericidal activity, and has a relatively wide environmental adaptation range and relatively long survival time. The bacteriophage vBValSR36H provided by the invention can specifically and effectively kill, prevent and control related vibrio diseases, meanwhile, virulence factor genes and drug-resistant genes are not detected in the bacteriophage, and the bacteriophage vBValSR36H has the advantages of no toxic or side effect, high safety, environmental friendliness and wide application prospect. Therefore, the vibrio alginolyticus bacteriophage vBValSR36H can be completely applied to killing and / or preventing vibrio alginolyticus for non-disease diagnosis and treatment purposes.

The invention discloses a road internal damage assessment method, device and equipment based on three-dimensional GPR data and a storage medium, and the method comprises the steps: determining a comprehensive disease weight corresponding to each disease in each layer of horizontal slice based on disease distribution feature information of a three-dimensional GPR horizontal slice data model, determining the internal damage rate of each layer of horizontal slice based on the comprehensive disease weight, determining the initial internal damage index of each layer of horizontal slice based on the internal damage rate, and performing through punishment correction on the through damage related layer to obtain the internal damage index; performing road internal damage evaluation on the road structure based on the internal damage index of each layer of horizontal slice; according to the method, the three-dimensional GPR horizontal slice data model is modeled, the disease distribution characteristics are analyzed in the horizontal direction, the three-dimensional geometric characteristics of the disease are accurately represented, the weight is objectively given to the disease, the internal damage index of each layer of horizontal slice is accurately calculated, and the internal damage of the road is accurately evaluated.

Described herein are novel and improved antibodies that bind to thymic stromal lymphopoietin (TSLP) and methods of use thereof. In certain aspects, described herein are methods of inhibiting TSLP biological activity. In certain aspects, the antibodies and methods described herein are used for treatment of an inflammatory disease or disorder associated with elevated levels of TSLP. In certain aspects, described herein are methods of treating asthma by administering anti-TSLP antibodies.

The invention discloses a crop disease multi-modal diagnosis and classification method and system, and relates to the technical field of data processing, and the method comprises the steps: collecting disease multi-modal data, and carrying out the preprocessing; constructing a disease multi-modal diagnosis model, respectively inputting images and text sequences in the multi-modal data into a visual feature extraction subnet and a text feature coding subnet of the disease multi-modal diagnosis model, and extracting global visual features, sequence state features and global text features; calculating a global matching score based on the global visual features and the global text features, executing fine-grained local interaction on the global visual features and the sequence state features, introducing a category channel attention mechanism to correct the features obtained by interaction, and weighting to generate multi-modal fusion features; and constructing a loss function based on the global visual features, the global text features and the multi-modal fusion features, training a disease multi-modal diagnosis model, inputting to-be-classified data into the disease multi-modal diagnosis model, and outputting a classification result.

The invention discloses a medical question-answering method, device, equipment and program product, and is applied to the technical field of medical question-answering. The method comprises the following steps: acquiring a disease image and disease chief complaint information; performing feature extraction on the disease image and the disease chief complaint information to obtain pathological visual features and chief complaint text features; performing feature fusion on the pathological visual features and the chief complaint text features to obtain target fusion features; determining a dynamic cue word template based on the information type of the target fusion feature; and inputting the dynamic cue word template and the disease image into a preset large language model, and generating a medical question and answer result by the large language model. According to the method, a complete, dynamic and adaptive cue word template is generated according to the consistency or conflict fuzziness embodied by the multi-modal information, so that the dynamic cue word template can further put forward a more complex task with question and answer guidance to a large language model, the pertinence and depth of medical question and answer are improved, and the medical question and answer efficiency is improved. And the precision of medical questions and answers is effectively improved.