38 results about "Established diagnosis" patented technology

A failure diagnostic apparatus determines the environment in which the condition of a vehicle is examined and selects an appropriate storage location for information regarding the condition of the vehicle. In particular, the failure diagnostic apparatus includes a vehicle-condition diagnostic portion, a plurality of failure-information storage portions, a diagnostic-environment determination portion, and a storage selection portion. When the vehicle-condition diagnostic portion determines that a failure has occurred, the diagnostic-environment determination portion determines the environment in which the condition of the vehicle is examined. Then, based on the diagnostic environment determined by the diagnostic-environment determination portion, the storage selection portion selects at least one storage portion of the plurality of failure-information storage portions to store information regarding the failure.

The present invention relates to a diagnosis assistance system for assisting diagnosis for a plurality of diseases based on a fundus image, the diagnosis assistance system including: a fundus image obtaining unit configured to obtain a fundus image; a first processing unit configured to, for the fundus image, obtain a first result related to a first finding of a patient using a first neural network model, a second processing unit configured to, for the fundus image, obtain a second result related to a second finding of the patient using a second neural network model, a third processing unit configured to determine, on the basis of the first result and the second result, diagnostic information on the patient, and a diagnostic information output unit configured to provide the determined diagnostic information to a user.

The invention relates to a computing device-implemented method and apparatus for unsupervised segmentation of microscopic color image of unstained specimen and digital staining of segmented histological structures. Image of unstained specimen is created by light microscope 101, recorded by color camera 102 and stored on computer-readable medium 103. The invention is carried out by a computing device 104 comprised of: computer-readable medium for storing and computer for executing instructions of the algorithm for unsupervised segmentation of microscopic color image of unstained specimen and digital staining of segmented histological structures. Segmented histological structures and digitally stained image are stored and displayed on the output storing and display device 105 in order to establish diagnosis of a disease. The invention is an improvement over the prior art as it is characterized by the: (i) shortening of slide preparation process; (ii) reduction of intra-histologist variation in diagnosis; (iii) elimination of adding chemical effects on specimen; (iv) elimination of altering morphology of the specimen; (v) simplification of histological and intra-surgical tissue analysis; (vi) being significantly cheaper than existing staining techniques; (vii) being harmless to the user because toxic chemical stains are not used; (viii) discrimination of several types of histological structures present in the specimen; (ix) usage of the same specimen for more than one analysis.

The invention belongs to the field of prognostic and health management (PHM) system integration and verification, and relates to an airborne equipment fault diagnosis and prediction model verificationmethod. The airborne equipment fault diagnosis and prediction model verification method is characterized in that BIT data, state parameters, configuration information and resume information reportedby each underlying LRU/LRM are simulated through carrying out simulation on member-level PHM, and an airborne equipment fault diagnosis and prediction model is loaded according to interface requirements; then the verified model is operated according to a model verification process; and finally, the diagnosis and prediction model in the PHM system is verified based on established diagnosis and prediction performance indicators, whether the relevant performance of the model meets technical indicators involved in the design requirements or not, and thus the verification for the airborne equipmentfault diagnosis and prediction model is realized. The method can be used for establishing a comprehensive verification platform of the PHM system, and reflects the engineering characteristics such asstandardization, systematicness, universality and practicability.

System and method provide an on-line high-performance diagnosis service for cardiovascular disorders. A client requests a high-performance diagnosis by transmitting real electrocardiographic treatment data and magnetocardiographic treatment data of a human body being a treatment object and virtual heart simulation parameters to a medical service server. The medical service server, in response to the diagnosis request, analyzes the real electrocardiographic treatment data to generate an electrocardiographic analysis result, and performs a virtual heart simulation using the simulation parameters to generate a pseudo electrocardiogram and magnetocardiogram. Further, the medical service server determines a disease state of the human body on the basis of the electrocardiographic analysis result, the magnetocardiographic treatment data and the pseudo electrocardiogram and magnetocardiogram, and generates definitive diagnosis data through comparison among the real magnetocardiographic treatment data, the electrocardiographic analysis result, the disease state, and a diagnosis criteria. The definitive diagnosis data is provided to the client.

A computer implemented system and method for matching drugs and diseases and generating a weighted relationship between the matched drugs and diseases. The system stores a quantity of patient medical history billing records identifiable as patient prescription claim records and medical claim records. The system also stores a grouping of drug codes and groupings of diagnosis codes. The system is configured to match drugs identified in a specific patient's prescription claim records with diseases identified in the patient's medical claims. The system generates a weighted relationship between the matched drugs and diseases by calculating a link weight in accordance with a preprogrammed formula for each occurrence of the diagnosis codes identified in the patient's medical claims that is identified as associated with the disease identified and the drug upon which the query is being processed. The link weight provides a statistical match association value to each of the matched diseases.

The diagnostic method is provided with no leakage of user's private information, less errors in reproduction of the setting status, and no performing of useless diagnoses. Input from a user is received by outputting a select object for limiting a diagnosis item of the diagnostic code generation terminal 10 to the diagnostic code generation terminal 10, a diagnosis item corresponding to the select object is determined in accordance with the input from the user, and performing diagnosis of the determined diagnosis item is performed. Then, a diagnostic code reflecting the result of the performed diagnosis is generated, and the setting status of the diagnostic code generation terminal 10 is reproduced by inputting the diagnostic code from an operator terminal 150. Even when a diagnostic code is repeatedly generated, information on the past diagnostic code is included in the next diagnostic code, and thus useless diagnosis processes are reduced.

The invention discloses an establishment method for an ADHD diagnosis model, a storage module and processing equipment. The ADHD diagnosis model is applied to ADHD identification. The method comprisesthe steps that firstly, a discrete electroencephalogram sample signal x(n) is acquired; then, the x(n) is subjected to five-layer wavelet decomposition of db5 wavelets, wavelet decomposition coefficient matrixes of a5, d5, d4, d3 and d2 scales are read, energy values of wavelet decomposition coefficients are calculated, an energy characteristic vector T is established, an electroencephalogram signal energy value Ej is uniformized, and a uniformized characteristic vector E'j is obtained so that a uniformized energy characteristic matrix can be obtained; finally, the uniformized energy characteristic matrix is used as input of an SVM classifier, a radical basis kernel function is used as a kernel function for mode identification of brain waves, and a training model after mode identificationis used as the ADHD diagnosis model. When the established diagnosis model is used for ADHD identification, the speed is high, and the accuracy rate is high.

In order to meet the performance maintenance requirement of SaaS software. The invention discloses a SaaS software performance fault diagnosis method based on a GBDT decision tree in combination witha performance log. A monitoring means is adopted to obtain a performance log when the software system runs. The performance fault type of the performance log is marked by combining the analysis resultof the warning log. the performance logs are processed by using a same type mean value filling method and a combined SMOTE and pre-sampling method; complete and balanced performance log data can be provided. A GBDT algorithm in a machine learning method is used for analyzing performance logs, a performance fault diagnosis model is established, the performance logs generated by a system in real time are input into the established diagnosis model, an output corresponding performance fault type is obtained, and therefore the performance state of the SaaS software in the running process is diagnosed. Besides, the real-time performance log and the diagnosis result can be saved, the diagnosis model can be updated every a period of time, the real-time performance of the diagnosis model is guaranteed, and the accuracy of the diagnosis result is further guaranteed.

An engine cylinder misfire detection system is provided that detects changes in exhaust manifold pressure (EMP) fluctuations, compares the EMP fluctuations with diagnostic thresholds determined with other engine characteristic information obtained from engine sensor data, and determines whether a cylinder misfire has occurred. A method of monitoring and detecting EMP fluctuations in combination with one or more sensed engine characteristics is disclosed to determine an engine cylinder misfire in a cycle of an internal combustion engine having at least one cylinder. The actuation approaches of the present invention include one or more processes for a cylinder of an engine associated with a determination of various load variables including fresh air flow, engine type, engine data inputs, and analytical determinants.

Provided are a diagnostic model generating apparatus and a diagnostic model generating method therefor. The diagnostic model generating method may comprising: extracting at least one keyword from consultation data between a user and a consultant for resolving electronic device errors; on the basis of the at least one extracted keyword, determining a diagnostic sequence between the plurality of diagnostic commands for resolving errors and a plurality of diagnostic commands; and storing a diagnostic model comprising the plurality of determined diagnostic commands and determined diagnostic sequence.

The embodiment of the invention discloses a medical record home page auditing method, device and equipment, and the method comprises the steps: recognizing a target medical record home page, and obtaining medical record basic information, diagnosis information and surgical operation information; acquiring expense detail information corresponding to the target medical record home page, and matching each medical service item contained in the expense detail information with the surgical operation information based on a pre-established mapping relationship between the surgical operation and the medical service item set to obtain a first auditing result; and acquiring a medical data set corresponding to the target medical record home page, acquiring a diagnosis matching rule set corresponding to each diagnosis based on a pre-established diagnosis matching rule base, and matching the diagnosis information, the medical data set and the diagnosis matching rule set corresponding to each diagnosis to obtain a second auditing result. By adopting the mode of the invention, the surgical operation information and the diagnosis information can be audited, and the hospital loss is reduced.

The invention relates to an electrical connector (1) for connecting an electrical device to an electrical conductor (3) for powering the electrical device with DC voltage. The electrical connector comprises a diagnostic information providing unit for providing diagnostic information about a connection between the electrical device and the electrical conductor and an indicator for indicating the determined diagnostic information. An installer can therefore readily see whether the electrical connection is correct or not. Accordingly, the installer can modify the electrical connections such that the indicated determined diagnostic information indicates a correct electrical connection. This reduces the likelihood of a shutdown of the powering of the electrical device with DC voltage, after the installation has been completed.

The invention discloses a nuclear power plant fault diagnosis method, a nuclear power plant fault diagnosis device and a medium, and provides a nuclear power plant fault diagnosis method for solving the problems that human errors cannot be avoided by adopting an expert system to assist manual monitoring at present and the judgment on the fault problem which does not occur before is inaccurate, and the method comprises the following steps: obtaining actual working condition data of a nuclear power plant; inputting the actual working condition data into a pre-established diagnosis model; and obtaining a diagnosis result output by the diagnosis model. As the diagnosis result is returned by the diagnosis model after the actual working condition data is input into the diagnosis model, manual participation is not needed, and human errors caused by manual monitoring are avoided. And the accuracy verification is performed on each LSTM model trained by the training set data through the verification set data, and the LSTM model with the highest accuracy is selected as the diagnosis model, so that the diagnosis model also has accuracy guarantee for the unseen data, and the fault diagnosis is more accurate compared with an expert system completely depending on previous artificial experience.

The invention discloses a project research and development capability diagnosis method and system, and the method comprises the steps: carrying out the data capturing of a data source through a thread, and forming a research and development data warehouse; the method comprises the following steps: cleaning research and development data in a research and development data warehouse to obtain structured data, inputting the structured data into a pre-established diagnosis model, performing overall diagnosis on the research and development project capability, and obtaining scoring information corresponding to a diagnosis result; based on scoring information corresponding to the diagnosis result, a scoring report is generated, and excellent items and problem points of related products are displayed; management personnel and project personnel can determine the future product research and development direction according to the current situation of the product clearly displayed by the diagnosis scheme, and a strategy is made for the project. And in the research and development implementation and improvement process, the change data of the returned warehouse is reflected in the diagnosis system again to form closed-loop management. According to the scheme, the problems that in the prior art, the research and development process capacity is not perceived, high-intensity analysis is achieved, and improvement measures are difficult to formulate are solved.

The invention is applicable to the technical field of medical services and provides a medical service method and system and terminal equipment. The method comprises the following steps of receiving medical detection data, wherein the medical detection data carries patient information; determining the information of physicians responsible for diagnosis and the information of physicians responsiblefor clinical reception according to the patient information; sending the medical detection data to a terminal for the physicians responsible for diagnosis according to the information of the physicians responsible for clinical reception and receiving a diagnostic analysis report sent by the terminal for the physicians responsible for diagnosis according to the medical detection data; sending the medical detection data and the diagnosis analysis report to a terminal for the physicians responsible for clinical reception according to the information of the physicians responsible for clinical reception; receiving a diagnosis and treatment scheme determined by the terminal for the physicians responsible for clinical reception according to the medical detection data and the diagnosis analysis report and sending the diagnosis and treatment scheme to the patient terminal according to the patient information. According to the method, the system and the terminal equipment, medical resources canbe reasonably configured, circulation of the medical detection data is realized, the diagnosis efficiency and the diagnosis quality are improved, and patients can see doctors conveniently.

The invention relates to a flowmeter verification method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining the feature data of a target flowmeter, and the feature data comprises the acceleration and the flow value of the target flowmeter; determining whether the state of the target flowmeter is abnormal or not according to the feature data; if the state of the target flowmeter is abnormal, diagnosis parameters of the target flowmeter are determined according to the feature data; according to the diagnosis parameters, abnormal reasons corresponding to the diagnosis parameters are searched in a pre-established diagnosis database, and the diagnosis database comprises the mapping relation between the diagnosis parameters of the template flowmeter and the abnormal reasons. According to the method, the abnormal vibration data of the target flowmeter can be monitored and recorded in real time, and the reason of the abnormal vibration of the target flowmeter can be diagnosed in time.