100results about How to "Easy diagnosis" patented technology

The invention discloses a characteristic value calculation method based on electrocardio data, belongs to the field of medical data analysis, and provides an electrocardio data analysis and processing method. Comprising the following steps: decomposing different frequency components of an electrocardiosignal by using wavelet transform, and analyzing on different time scales. Wavelet transformation is relatively suitable for detecting QRS wave groups, and due to the fact that the wavelet transformation can highlight transient characteristics of signals on different frequency bands, complex electrocardiosignal processing is more efficient. In addition, wavelet transform is not only suitable for wave crest detection, but also can help to remove signal noise and improve signal definition. The deep learning technology is used for automatically extracting the features from the electrocardiosignals, a feature extractor does not need to be manually designed, related medical professional knowledge and the artificial intelligence technology are combined, wave crests in the electrocardiosignals can be more accurately detected, and meanwhile anomaly detection can be carried out, such as early signs of heart diseases such as sinus arrhythmia and the like.

The invention discloses a rheumatoid arthritis diagnosis product and system and application thereof, and relates to the technical field of rheumatoid arthritis. The diagnostic marker comprises calcium, a ratio of arginine to ornithine, a ratio of phenylalanine to tyrosine, an anti-cyclic citrullinated peptide antibody and lysine. The invention provides a biomarker capable of accurately diagnosing rheumatoid arthritis RA, which comprises five indexes, namely calcium, the proportion of arginine to ornithine, the proportion of phenylalanine to tyrosine, an anti-cyclic citrullinated peptide antibody (anti-CCP) and lysine. The five indexes have the technical advantages of few indexes and excellent diagnosis performance. A diagnosis model constructed based on the five indexes has good sensitivity, specificity and accuracy. The kit can be used for diagnosis of rheumatoid arthritis.

The invention provides a vehicle diagnosis method and device, a chip, a vehicle, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving a first hypertext transfer protocol HTTP request message sent by diagnosis equipment; wherein the first HTTP request message is used for requesting a target resource in the target node; the communication protocol used by the target node is a unified diagnostic service UDS communication protocol; the first HTTP request message is converted into a UDS request message, and the UDS request message is sent to a target node; receiving a UDS response message sent by the target node; wherein the UDS response message comprises resource information of a target resource in the target node; and converting the UDS response message into a first HTTP response message, and sending the first HTTP response message to the diagnostic device. According to the invention, the method can be better suitable for the whole vehicle topology which is high in HPC node occupation ratio and is added with Ethernet connection; and meanwhile, the node using the UDS communication protocol in the vehicle can be diagnosed.

The invention discloses an image CT (Computed Tomography) image enhancement method and system. The image enhancement method comprises the following steps: acquiring a CT image; preprocessing the CT image to obtain a feature vector; clustering different tissue structures in the CT image based on the feature vectors to obtain tissue structure images corresponding to different categories; and performing saturation transparent adjustment on the tissue structure image to obtain an adjusted CT image. The visual difference of the tissue structure can be enhanced from multiple angles, the overall quality and readability of the CT image are improved, and clear and accurate information support is provided for image observation and diagnosis of doctors.

The invention belongs to the technical field of intelligent diagnosis of mental diseases, and particularly relates to a major depression diagnosis system. The system comprises an input module used for inputting indexes of a patient; wherein the indexes comprise at least one of the following information: a neurocognitive test, child trauma information, multi-modal neuroiconomics information and transcriptomics information; the prediction module is integrated with a machine learning model and is used for obtaining a prediction result about whether the patient suffers from the major depression or not according to the indexes; and the output module is used for outputting the prediction result. The system provided by the invention can accurately diagnose the major depression, can effectively assist doctors in diagnosing and screening the major depression, reduces the workload of workers, and has a very good application prospect.

The invention relates to a magnetic suspension bearing control system and method and refrigeration equipment, and the system comprises a magnetic suspension bearing control module which is used for controlling a magnetic suspension bearing; the battery management module is electrically connected with the magnetic suspension bearing control module; and the master control module is respectively connected with the magnetic suspension bearing control module and the battery management module and can control the battery management module to store electric energy when the voltage of the magnetic suspension bearing control module is excessive and supply power to the magnetic suspension bearing control module when the power supply of the magnetic suspension bearing control module is insufficient. According to the technical scheme of the magnetic suspension bearing control system, through cooperative work of the battery management module and the master control module, the stability, the energy-saving performance and the response speed of the system are enhanced, the service life of equipment is effectively prolonged, and the maintenance cost is reduced. The integrated solution provides a safer, more reliable and more economical operating environment for high-performance and high-precision mechanical equipment.

The invention discloses a transformer current rising experiment method, which comprises the following steps of forming an experiment transformer through parallel compensation of a capacitor and a transformer, and providing capacitor current response for the experiment transformer by using the capacitor; constructing an equivalent inductance model and an equivalent capacitance model; applying an initial current response according to a rated current response of the transformer, calculating a capacitor current response, and adding a nonlinear element to obtain a nonlinear voltage response; updating the capacitor current response based on the nonlinear voltage response to obtain an updated capacitor current response; under the condition of considering the temperature effect, updating the updated capacitor current response again based on an equivalent inductance model to obtain a final capacitor current response; performing asynchronous frequency modulation, and updating the voltage response to obtain an updated voltage response; and calculating an experiment result based on the updated voltage response. The device is suitable for the transformer current rising experiment.

The invention discloses a plasma protein-based stomach cancer early-stage multi-molecular diagnosis model construction method, and aims to solve the problems that the existing stomach cancer early-stage diagnosis standard and minimally invasive or non-invasive method are imperfect, the sensitivity and specificity of the existing diagnosis molecular marker are low and the like, an Olink proteomics PEA technology is utilized and a specific detection panel is selected to construct a stomach cancer early-stage multi-molecular diagnosis model. And identifying the protein markers of gastric cancer, early gastric cancer and gastric precancerous lesions in a discovery queue (n = 88). In a discovery queue, a group of multi-protein molecular marker models consisting of 13 proteins are successfully identified by utilizing an LASSO regression model, and the multi-protein molecular marker models have good diagnostic performance for distinguishing gastric cancer, early gastric cancer and pregastric lesion and contrast in the discovery queue and verification pair. Furthermore, in a verification queue sample, the diagnosis model also shows good diagnosis performance, and the marker model is expected to become a powerful tool for early diagnosis of gastric cancer.

The utility model discloses an LED endoscope cold light source which comprises a main machine shell and a light transmitting bundle, the front vertical face of the main machine shell comprises an inclined face and a vertical face, a control module is arranged in the main machine shell, the control module is in communication connection with an LED light source module and a display module, a light through hole is formed in the vertical face, and a connecting assembly is fixedly arranged outside the light through hole. A shaft hole is formed in the lower portion of the light through hole, a rotating shaft is arranged in the shaft hole in a matched mode, a round color temperature adjusting plate is fixedly connected to the end, located in the main case, of the rotating shaft, the round color temperature adjusting plate is located between the LED light source module and the light through hole, and a turncap is connected to the end, located outside the main case, of the rotating shaft. By adjusting the circular color temperature adjusting plate, the purpose of changing the color temperature of the LED light source is achieved.

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

The application provides an industrial equipment fault diagnosis model construction method and related equipment, and relates to the technical field of industrial equipment fault diagnosis. The method comprises the following steps: obtaining a physical mechanism model of the industrial equipment; the physical mechanism model comprises a physical constraint equation; constructing a deep learning network; the deep learning network comprises a composite loss function constructed according to the physical constraint equation; collecting full-time series state data of the industrial equipment during operation; the full-time series state data comprises specified time series state data collected when the industrial equipment is in a healthy state; based on the full-time series state data, the deep learning network is trained for parameter optimization to obtain a final available industrial equipment fault diagnosis model. The method of the application aims to solve the problems of weak early fault identification ability, poor interpretability, lack of physical meaning and strong data dependence in the existing industrial equipment fault diagnosis technology, and effectively improves the intelligent level and operation and maintenance efficiency of the industrial equipment fault diagnosis.

The utility model relates to the technical field of cosmetic mirrors, and discloses a combined cosmetic mirror which comprises a base, the top of the base is fixedly connected with a driving mechanism, the top of the driving mechanism is fixedly connected with a rear lamp box, the interior of the rear lamp box is fixedly connected with a lighting mechanism, and the driving mechanism comprises a driving guide rail. The bottom of the driving guide rail is fixedly connected to the interior of the base, the top of the driving guide rail is fixedly connected with a light supplementing assembly, and the top of the driving guide rail is fixedly connected with a supporting display assembly. According to the utility model, the top of the base is provided with the driving guide rail, the driving guide rail drives the front lampshade to move along the track, meanwhile, the side light supplementing lamp ring moves along with the driving guide rail, the front lampshade is fixed by the locking piece to be kept at different positions, the light supplementing distance is flexibly adjusted, the light supplementing effect is uniform, various make-up scene requirements are met, and the flexibility is improved; and the light supplementing effect is effectively improved, and the requirements of different make-up scenes are met.

The invention relates to the technical field of nucleic acid detection, in particular to an LAMP-CRISPR visual detection method for identifying a monkey pox virus based on an ATI gene and a kit and application of the LAMP-CRISPR visual detection method. Preparing an LAMP system and a CRISPR system, wherein the LAMP system and the CRISPR system are separated through mineral oil and air; carrying out LAMP amplification reaction to obtain an amplification product; adding an amplification product into a CRISPR (clustered regularly interspaced short palindromic repeats) system for enzyme digestion and visualization; wherein the reaction container comprises a PCR (Polymerase Chain Reaction) tube with the capacity of 200 mu L; the thickness of the mineral oil is 2.5-3mm; the air thickness ranges from 11 mm to 12 mm; the LAMP system is prepared at the bottom of the reaction container, the mineral oil is positioned on the upper surface of the LAMP system, and the CRISPR system is prepared in a circular groove of a tube cover of the PCR reaction tube. According to the detection method, a reaction system for visual detection is designed aiming at a monkey pox virus specific detection target, and an LAMP amplification system and a CRISPR detection system which are integrated into one tube are separated by utilizing mineral oil and liquid surface tension, so that not only is the detection convenience improved, but also the influence of high temperature during LAMP amplification on enzyme of the CRISPR detection system can be avoided.

This invention discloses a method and system for fault diagnosis of industrial equipment under complementary label constraints, belonging to the field of industrial intelligent operation and maintenance and fault prediction health management technology. The method includes: collecting and preprocessing equipment vibration signals; constructing a dual-head deep network based on one-dimensional residuals as a complementary label learning model; generating a joint probabilistic loss function using complementary labels based on maximum likelihood estimation, enabling the model to learn fault features from "negative" labels; and achieving high-precision fault classification using the trained model. This invention applies the complementary label learning paradigm in weakly supervised learning to industrial equipment fault diagnosis, achieving a diagnostic accuracy of over 90% on multiple standard bearing datasets such as CWRU and MFPT. This method significantly reduces the data labeling threshold and effectively solves the pain points of scarce fault samples and difficult labeling in industrial scenarios, possessing significant practical application value.

A residual-knowledge-data jointly driven fault composite diagnosis method and system, in which the first step is to construct a probability graph model, including determining the structure and parameters of the probability graph model, and the second step is to apply the probability graph model online, calculate the online real-time monitoring data, and input the residual data of the features in the residual nodes, the direct monitoring data of the features in the data nodes, and the state of the features in the knowledge nodes into the probability graph model to obtain the posterior probability of each state of the diagnosis layer node, and output the state with the maximum posterior probability in the diagnosis layer as the fault diagnosis result; the system includes a memory and a processor, and the processor executes a computer program to implement the above method. The present invention integrates the advantages of the three types of methods, namely, residual-driven, knowledge-driven, and data-driven, into the same diagnostic system, realizes the complementary advantages of each other, and obtains better diagnostic performance.

According to the application of the urine TRPV5 as the biomarker in chronic kidney disease diagnosis and risk assessment, it is found for the first time that the TRPV5 and the detectable fragment thereof exist in the urine, the content of the TRPV5 and the detectable fragment thereof in the urine is in positive correlation with the chronic kidney disease CKD, the CKD can be diagnosed by detecting the content of the TRPV5 in the urine, and the application of the TRPV5 and the detectable fragment thereof in the diagnosis and risk assessment of the chronic kidney disease in the diagnosis and risk assessment of the chronic kidney disease is achieved. The invention also provides a specific in-vitro diagnosis method and a kit. According to the in-vitro diagnosis method, multiple defects of the existing CKD diagnosis technology are overcome, a brand-new diagnosis tool which is noninvasive, sensitive and specific and can be used for staging and prognosis evaluation is provided, and the in-vitro diagnosis method has remarkable scientific and technological advancement and wide clinical application prospects.

The utility model provides a kind of air conditioner soft-start control system, air conditioner starting interface, current detection module, power control unit, bypass unit, temperature detection module, through bypass unit through soft-start, start smooth, reliable operation, when magnetic retainer B is attracted, the trigger signal of thyristor SCR3, thyristor SCR4 is removed, thyristor SCR3, thyristor SCR4 stop conducting, compared with traditional contactor in entire bypass conduction period needs to continue coil power supply, can realize significant energy saving, system long-term operation total energy consumption is greatly reduced, while avoiding coil continuous heating problem, it is favorable to improve system overall reliability and reduce heat dissipation demand;While setting phase-loss protection module, distinguish zero line loss and fire line loss etc. Fault type, accurate trigger protection and store fault code, diagnosis is convenient.

A radiotherapy system comprises a neutron acceptor, an atomization device for aerosolizing the neutron acceptor and an energy beam generator. The invention relates to a use of an aerosolized neutron receptor for preparing a medicament for treating cancer in an individual irradiated by neutrons. Use of an aerosolized radiopharmaceutical for the preparation of a medicament for diagnosing cancer in a subject in need thereof, comprising administering to the subject an effective amount of the radiopharmaceutical and receiving an energy beam signal from the subject. A method for delivering a neutron receptor to an individual during radiation therapy comprises aerosolizing the neutron receptor and administering an effective amount of the neutron receptor to the individual.

The present invention discloses a fault diagnosis method for measurement and control equipment based on a model, which specifically includes the following steps: S1, model definition; S2, logic definition; S3, directed graph conversion; S4, traversal positioning: The present invention relates to the field of aerospace measurement and control technology. The fault diagnosis method for measurement and control equipment based on a model uses processing functions and observation functions as basic mathematical models for single node fault diagnosis, establishes all the mutual relations between input and output signals of various functional modules inside the measurement and control equipment system, realizes the description of all possible states inside the measurement and control equipment system, can cover all possible faults of the measurement and control equipment system, and adopts a method for describing the mutual relations between various functional modules of the measurement and control equipment system with a directed graph, realizes rapid diagnosis and precise positioning of functional module faults through directed graph search, and the diagnosis model is relatively simple, the combination process is not complicated, and has good scalability.

The application of the biomarker combination in the preparation of a drug for fulminant myocarditis belongs to the field of drugs. The application is characterized in that the biomarker combination comprises Siglec-5; the biomarker combination is further selected from the group consisting of sST2, PAI-1, Siglec-5, CD163, CD40, P-Cadherin, CD14, CTLA4. The application finds that the expression of the biomarker in the plasma of a patient with fulminant myocarditis is increased, and confirms the role of the biomarker as a drug target in relieving and / or improving fulminant myocarditis. The level of the biomarker can be controlled by a drug, the diagnosis and subsequent treatment of the disease can be more intensified, and the biomarker has great application value in clinical practice.

The application provides a biomarker for assisting in diagnosing systemic lupus erythematosus and application thereof, proves that 15(S)-HETE has good diagnostic efficiency for systemic lupus erythematosus, and the diagnostic efficiency is improved after 15(S)-HETE is combined with anti-dsDNA antibody or anti-Smith antibody, has good diagnostic efficiency for systemic lupus erythematosus with negative specific autoantibody, and 15(S)-HETE can also reflect the disease activity of systemic lupus erythematosus.

This invention relates to solenoid valve fault diagnosis technology and discloses an automotive intelligent chassis electronic control system and its control circuit. The system includes a first fault diagnosis circuit and a second fault diagnosis circuit, each comprising a voltage acquisition unit, a voltage divider circuit, and a protection circuit. The protection circuit protects the fault diagnosis circuit, the voltage divider circuit divides the voltage output by the solenoid valve, and the voltage acquisition unit acquires the divided voltage. The voltage of the solenoid valve is acquired in real time using the voltage acquisition unit, and the state of the solenoid valve is determined based on the acquired voltage. This invention diagnoses faults in the solenoid valves of the automotive intelligent chassis electronic control system without requiring a driving solenoid valve. Each solenoid valve diagnosis requires only one port resource, making the diagnostic method simple and low-cost.

The utility model discloses an AI acceleration computing server stable in operation, which comprises a support frame, a fan in a mounting frame is used for cooling a server main body to keep the server stable in operation, a worm on one side of the support frame is rotated to enable a worm gear meshed with the worm to drive a rotating rod to rotate, and the rotating rod rotates to drive the server main body to rotate. The angle of the server main body above the mounting plate can be adjusted through the rotation of the rotating rod, so that the server main body can face a worker, the fan which is moved out can be conveniently observed and diagnosed, and the convenience of maintenance is improved; a first lead screw above a server body is rotated, a first connecting frame in threaded connection with the first lead screw can drive a mounting frame to move, a draught fan on the inner side of the mounting frame can be moved out of the server body, meanwhile, the first connecting frame is located above the draught fan, an LED spotlight on the first connecting frame can illuminate the draught fan, and a second lead screw above the first connecting frame is rotated, so that the draught fan can be conveniently and rapidly moved out of the server body. The position of the LED spotlight in threaded connection with the second lead screw can be adjusted, and it is guaranteed that illumination is sufficient in a key area.

This invention discloses a protein biomarker for assisting in the early diagnosis of acute myocardial infarction and its application. The biomarker is characterized by being at least one of GLRX, CA1, EIF4EBP1, MYL4, SOD1, BOLA2_BOLA2B, DDT, TNNI3, GH1, ACY1, POMC, AK1, FABP3, YOD1, GLO1, RANBP1, TGM2, PLPBP, OLR1, CEACAM8, CD2AP, AAMDC, and QDPR. The invention also provides the application of the above-mentioned protein biomarkers in the preparation of early diagnostic reagents or kits for myocardial infarction. The advantages are that it allows for convenient and rapid diagnosis of early AMI at the molecular level, with high detection efficiency, high sensitivity, and strong specificity, which is beneficial for the early detection and timely treatment of AMI patients.

The invention relates to the technical field of subway monitoring, in particular to an automatic subway monitoring and early warning system based on artificial intelligence, which comprises a hygrothermograph, an ultrasonic radar, a thermal imager and a central processing module, the central processing module corrects the tunnel ultrasonic point cloud according to the temperature in the tunnel and the relative humidity in the tunnel and generates a temperature position point cloud after registering the tunnel infrared image with the ultrasonic point cloud, and the difference between the temperature position point cloud and a laser point cloud in the prior art is that each point in the temperature position point cloud has a corresponding temperature. The temperature position point cloud represents the tunnel structure and also represents the temperature distribution in the tunnel, and the technical feature of the temperature position point cloud helps a subway monitoring neural network model to more easily diagnose tunnel diseases caused by temperature changes. According to the invention, the multi-modal fusion technology, the ultrasonic point cloud scanning technology and the infrared imaging technology are combined to realize multi-modal, moisture-resistant and high-reliability metro automatic monitoring and early warning.

The invention relates to an exhaust brake electromagnetic valve. According to the electromagnetic valve, a main gas circuit unit, a proportional electromagnetic driving structure, a gas circuit switching structure and a gas pressure detection structure are integrated. Continuous and linear accurate adjustment of output air pressure is realized through a proportional electromagnetic driving structure; the gas path switching structure can intelligently switch gas flow between the first gas outlet and the second gas outlet according to an instruction; the pressure sensor integrated in the valve body monitors the actual output air pressure in real time, closed-loop feedback control is formed, and accurate matching of braking force is ensured. The system is compact in structure, remarkably reduces external pipelines and leakage points, has the advantages of being rapid in response, accurate in control, high in reliability and high in adaptability, and remarkably improves the smoothness and safety of vehicle braking.

The application provides a plasma exosome mRNA biomarker and application thereof in construction of a gastric cancer diagnosis model, and relates to the technical field of biological medicine.The application first discovers that plasma exosome mRNA MORC3 is significantly enriched in plasma of gastric cancer patients, indicating that the plasma exosome mRNA MORC3 is expected to be used as a biomarker for gastric cancer diagnosis and as a target gene for treatment of gastric cancer.We take the plasma exosome mRNA MORC3 as a target marker to construct a diagnosis model and a corresponding diagnosis system for gastric cancer.The diagnosis model provided by the application shows high sensitivity and specificity in distinguishing gastric cancer patients from healthy people, displays good diagnosis efficiency, and can effectively identify gastric cancer patients, thereby providing an effective auxiliary tool for clinical diagnosis.The application provides a new choice for a molecular marker for gastric cancer diagnosis, overcomes the low sensitivity of existing cancer markers when used for gastric cancer diagnosis, and provides a new method for early screening and diagnosis of gastric cancer.

The invention relates to the technical field of hydrological data analysis, and provides a runoff reanalysis data error analysis method and system based on panel regression analysis, and the method comprises the following steps: collecting a watershed hydro meteorological data set, watershed runoff reanalysis data and meteorological reanalysis data, extracting drainage basin runoff reanalysis time series data and drainage basin meteorological reanalysis time series data; constructing a fixed effect panel regression model of the meteorological input deviation and the runoff simulation deviation based on the deviation between the reanalysis data and the observation value; the method comprises the following steps of: clustering all drainage basins according to drainage basin site attribute data to obtain spatial clusters of the drainage basins and attribute characteristics of each cluster, resampling each cluster through a bootstrap method to form first panel data, performing fixed effect panel regression on the first panel data to obtain a corresponding regression coefficient, and performing fixed effect panel regression on the first panel data to obtain a regression result; a first coefficient distribution for measuring spatial heterogeneity effects of meteorological deviations is generated.

This invention discloses a method and apparatus for detecting and diagnosing energy storage devices based on multi-model fusion and AI collaboration. The method starts a portable host, drives the detection modules to perform self-tests, initializes the AI ​​processing module, and establishes a connection by scanning surrounding devices using the communication module. Voice commands control each detection module to collect multi-dimensional raw data. Each diagnostic model quantitatively calculates and outputs single-dimensional diagnostic results and confidence levels. A weighted fusion of these results using a self-built core fusion model yields a comprehensive diagnostic value, determining the fault level and type to generate a comprehensive diagnostic result. Protocols are parsed as needed to generate adaptation code, supplementing the collection of auxiliary data. The optimal operation and maintenance solution is selected based on the comprehensive diagnostic result using formula calculations, outputs the solution, and drives its execution. Data is simultaneously uploaded to the cloud. Finally, model parameters and weight coefficients are updated based on the device's operating data after fault handling, improving subsequent diagnostic accuracy. This invention solves the problems of difficult cross-manufacturer interface adaptation and inefficient operation in extreme environments found in existing technologies.

The application discloses a capsule endoscope control system and a recording method and a playback method thereof, and the system comprises a magnetic ball and a control device, the position and posture change of the magnetic ball causes the magnetic field change, so that the capsule endoscope moves along with the magnetic field change; the control device is connected with the magnetic ball, controls the position and posture change of the magnetic ball, and processes the posture parameters and image information of the capsule endoscope, wherein the control device acquires the state parameters of the magnetic ball, the posture parameters and image information of the capsule endoscope in real time during the examination by the capsule endoscope, and generates the operation record of the state parameters of the magnetic ball, the operation information of the control device and the posture parameters and image information of the capsule endoscope along with the change of time, and converts the operation record into a command sequence to write the storage data. Therefore, the operability of the automatic examination of the capsule endoscope is improved, the repeatability of the recording process and the effectiveness of the examination effect can be considered, and the training efficiency can be effectively improved in professional training.