42 results about "Secondary diagnosis" patented technology

The invention provides a diagnosis related grouping method and system based on coding intelligent adaptation. The method comprises the following steps: (1) pretreating the case data, and separately extracting the diagnosis information and operation information of the case; (2) establishing a dynamically expanded keyword library, and intelligently matching the diagnosis information and the operation information of the case to obtain a diagnosis adapting code and an operation adapting code; (3) inputting the diagnosis adapting code as the primary or secondary diagnosis code of the case and the operation adapting code into a case grouping system; and (4) grouping the diagnosis adapting code and the operation adapting code, and outputting a diagnosis related grouping result of the case. According to the invention, the problem that the diagnosis related grouping scheme is hard to implement in medically underdeveloped areas is solved fundamentally, upper and lower layers of DRGs grouping results can be obtained according to local medical cost data, and the results better fit the local actual conditions of medical treatment while the comparability and flexibility are both realized.

The invention provides a mental disorder diagnosis and treatment system based on artificial intelligence. The system comprises a patient end system, a therapist end system and an intelligent auxiliarysystem. The patient end system collects patient information and sends it to the intelligent auxiliary system for communication between the patient and the therapist. The intelligent auxiliary systemestablishes data interaction between the patient end system and the therapist end system, obtains the initial diagnosis result according to the patient information and sends the related data to the patient end system and the therapist end system. In the process of communication between the patient and the therapist, the intelligent auxiliary system recognizes the communication content, collects the patient information for the second time and processes the data collected twice to obtain the secondary diagnosis result and obtains the recommended treatment scheme according to the relevant data and sends the secondary diagnosis result and the recommended treatment scheme to the therapist end system. The therapist end system displays the patient information and the intelligent computing resultto the therapist for the therapist to communicate with the patient and sends the final diagnosis result and the treatment scheme to the patient. The diagnosis and treatment system can reduce the workload of the therapist.

The invention discloses an infrared database intelligent diagnosis management system for charged equipment. The system comprises a transformer station operation platform, an intelligent data diagnosis processing center, an infrared dedicated engineer operation platform and a high-level inquiry monitoring platform. A supervisor and an infrared dedicated engineer can log on a remote WEB browser endto view infrared detection reports uploaded by a transformer station, know an equipment operation situation, view historical data, defect reports and equipment historical temperature trend curves, perform secondary diagnosis on equipment defects by using an intelligent diagnosis and auxiliary decision system, query by taking equipment of a certain factory as a condition to obtain all infrared charts of defective equipment, and provide reference for later purchase by comparing the quality of the equipment of different factories laterally. Transformer station staff can handle defects in time, upload the infrared detection reports and generated historical temperature trench curves, receive a superior indication, and perform emergency processing in time.

A plant diagnosis system friendly to a user (a plant-operating organization) for identifying an abnormality of an objective plant or machinery thereof, is provided. The plant diagnosis system includes a diagnoser's sub-system including a diagnosis computer and a terminal for a diagnosis expert and is connected via a network to a user's sub-system including a terminal for communicating with the diagnoser's sub-system. The plant diagnosis system provides a simple but repetitively available primary diagnosis and a detailed secondary diagnosis including the expert's judgement, which are selectively available on the user's initiative. The diagnosis computer receives a diagnosis request and plant state variables of the plant or machinery and executes the primary diagnosis and a part of the secondary diagnosis based on the plant state valuables.

The invention provides a novel power transformer fault combined diagnosis model building method and a fault diagnosis method; the diagnosis model building method comprises the following steps: using at least two of the following diagnosis models to primarily diagnose the oil dissolving gas analysis data: a Naive Bayes diagnosis model, a RVM diagnosis model and a matter-element diagnosis model; carrying out weighted average for the primary diagnosis result, using the secondary RVM diagnosis model to make the secondary diagnosis, thus obtaining the combined diagnosis model; using the combined diagnosis model to make fault diagnosis. The method can fully utilize advantages of various diagnosis models, thus effectively improving the diagnosis precision and validity.

The invention discloses an instrument remote fault diagnosis system based on internet of things and cloud computing. The instrument remote fault diagnosis system is composed of an instrument fault diagnosis center and multiple instrument monitors. The instrument fault diagnosis center comprises a wireless gateway, a cloud server, a fault database, a remote client terminal and a diagnosis expert terminal. Each instrument monitor comprises a wireless communication module, an instrument state monitor, an instrument information reader, a fault displayer, a power supply, an instrument running operation system, an alerter and a microprocessor. The instrument remote fault diagnosis system has characteristics of being simple in structure, intelligent, humanized and scientific and high-efficiency so that fault monitoring and fault diagnosis can be accurately performed on various instruments and equipment in enterprises in real time, and targeted and scientific diagnostic opinions can be provided to the generated faults via the cloud server and the fault database. Besides, an expert secondary diagnosis system is also introduced in the system so that accuracy of fault diagnosis is greatly enhanced.

The invention discloses a method for preventing battery failure false alarm and an apparatus thereof. The method comprises the following steps: determining whether a battery is fault or not by monitoring performance parameter of the power battery; when the power battery is fault, whether secondary diagnosis condition is satisfied or not can be determined; when the secondary diagnosis condition is satisfied, a fault power battery monomer is determined in the power battery; a battery module group of the fault power battery monomer is determined; according to the abnormal performance parameter of the fault power battery monomer and the performance parameter of the other power battery monomer in the battery module group of the fault power battery monomer, whether the power battery fault is the false alarm or not can be determined; when the power battery fault is determined as false alarm, false alarm is removed, and the false alarm of the power battery fault is avoided.

Disclosed is a diagnostic processing system including an onboard terminal system and a server connected together via radio communication channels. The onboard terminal system is provided with a data receiving unit for receiving data from sensors arranged on a self-propelled machine and a first diagnostic unit for diagnosing an abnormality of the self-propelled machine, and the server is provided with a second diagnostic unit for diagnosing the abnormality of the self-propelled machine. The diagnostic processing system is configured such that one of the first diagnostic unit and second diagnostic unit performs a primary diagnosis as to the abnormality of the self-propelled machine based on the data received at the data receiving unit and transmits a result of the primary diagnosis to the other diagnostic unit, and upon receipt of the result of the primary diagnosis, the other diagnostic unit performs a secondary diagnosis based on the result of the primary diagnosis.

The invention discloses a mining drill fault intelligent identification method which mainly comprises a primary diagnosis based on signal processing and a secondary diagnosis based on hybrid intelligence. According to the primary diagnosis based on signal processing, signal processing methods such as time domain and frequency domain analysis, wavelet packet analysis and empirical mode decomposition are utilized to extract a drill fault feature, a characteristic value is obtained through calculating and doing statistics, and a drill fault is judged preliminarily. According to the secondary diagnosis based on hybrid intelligence, the feature of the primary judgment is taken as an input, a support vector machine, an expert system, a fault tree analysis are used to diagnose the drill fault, and a diagnosis result is obtained by using voting technology. According to the mining drill fault intelligent identification method, a plurality of signal processing technology and intelligent diagnosis methods are integrated, the accuracy of drill fault diagnosis can be effectively raised, the examination and repair times are reduced, and the drilling cost is reduced.

The invention discloses a power distribution network fault diagnosis system and method based on a CIM model. Secondary diagnosis and judgment are performed on a result of fault positioning, thus the accuracy of power distribution network fault diagnostic analysis can be further improved, and at the same time, RSA encryption and a digital signature algorithm are utilized to perform confidential treatment on data transmitted through an interface, thereby improving information security and confidentiality. Based on an IPX / SPX network high-speed transport protocol, data transmission efficiency is improved, and high efficiency of big data transmission is satisfied. Through extension of a distribution network emergency maintenance platform in a medium- and low-voltage power supply path fault, fault control is practically performed on an overall power supply path of the distribution network, thereby facilitating safety command by a regulation and control center and on-site interaction, and improving the lean level of emergency maintenance.

A plant diagnosis system friendly to a user (a plant-operating organization) for identifying an abnormality of an objective plant or machinery thereof, is provided. The plant diagnosis system includes a diagnoser's sub-system including a diagnosis computer and a terminal for a diagnosis expert and is connected via a network to a user's sub-system including a terminal for communicating with the diagnoser's sub-system. The plant diagnosis system provides a simple but repetitively available primary diagnosis and a detailed secondary diagnosis including the expert's judgement, which are selectively available on the user's initiative. The diagnosis computer receives a diagnosis request and plant state variables of the plant or machinery and executes the primary diagnosis and a part of the secondary diagnosis based on the plant state valuables.

The invention relates to the field of computer-aided diagnosis, in order to improve the utilization rate of projection data information, and at the same time highlight the lesion position, which is conducive for doctors to carry out secondary diagnosis, and promote the further development of precision medicine. For this reason, the technical proposal adopted by the invention is a computer image processing method oriented to a medical CT, which comprises the following steps: Step 1: constructing a data set; Step 2: partitioning the dataset; Step 3: training convolution neural network; Step 4: testing the network training effect. The invention is mainly applied to the design and manufacture of computer-aided diagnosis medical equipment.

The invention relates to a preliminary diagnosis and treatment system. The preliminary diagnosis and treatment system comprises a database unit and a storage unit, wherein the database unit is used for storing information of currently known diseases; the information includes disease names, disease causes, disease symptoms, detection methods, therapeutic schedules and therapeutic effect thereof; the database further can be pre-set by a user according to own experience and be updated online; and the storage unit is used for storing personnel information of patients, such as names, genders and ages, and related information including disease diagnosis and medicine suggestion, secondary diagnosis suggestion and the like, so that doctors can use the stored information as reference information in a diagnosis process at a later period. The system is simple in structure and rapid and convenient to use, can provide necessary data instructions in the aspects of diagnosis and medicine use at any time and can improve the accuracy of diagnosis and medicine use. With the adoption of the system, patients can carry out the preliminary diagnosis at home and judge whether to go to hospital for further treatment or not. Therefore, the patients do not need to go to hospital when they do not need so that time and labor are saved; and relevant records of the preliminary diagnosis can be stored in the system and can be searched in the future.

The invention discloses a method for homoepitaxially growing a monocrystalline diamond on the basis of a type IIa natural diamond. The method includes the following steps: (Step 1) a reactor for producing a monocrystalline diamond material is provided; (Step 2) the type IIa natural diamond serving as a seed crystal is placed onto a sample holder of the reactor, treating gas is injected into a reaction chamber, plasma is utilized to etch the type IIa natural diamond, and an emission spectrum is utilized to carry out primary diagnosis; (Step 3) the technological parameters of the reactor are adjusted, the homoepitaxial growth of the monocrystalline diamond is carried out, and an emission spectrum is utilized to carry out secondary diagnosis; (Step 4) the deposition of the monocrystalline diamond is completed. By utilizing the microwave plasma chemical vapor deposition method to etch the type IIa natural diamond at high temperature and utilizing a produced carbon source to grow the diamond, the method can effectively increase the purity of the carbon source needed by the growth of the monocrystalline diamond, so the quality of the obtained monocrystalline diamond is good; and moreover, the grown monocrystalline diamond is of a regular shape corresponding to a substrate, so the utilization rate is increased.

The invention provides a battery fault diagnosis method. The method comprises steps: determining whether a power battery unit is faulty preliminarily by monitoring performance parameters of a power battery; if so, carrying out secondary diagnosis on the power battery unit; and sending out alarm information under the condition of determining the fault existence of the faulty power battery unit in the secondary diagnosis. Therefore, the accuracy of determining the battery fault is improved. In addition, the invention also provides a battery fault diagnosis apparatus and an electric vehicle.

The invention discloses a code recommendation method and system, corresponding equipment and a storage medium. The method comprises the steps: obtaining a medical record home page diagnosis text as the input of a trained first sub-eye inference model, the diagnosis text at least comprises a main diagnosis text, wherein the first sub-eye inference model comprises a deep learning language model anda sub-eye projection layer linked with the output of the deep learning language model, and the deep learning language model is used for at least outputting a main diagnosis semantic vector based on aninput diagnosis text; in response to the fact that the diagnosis text does not include the secondary diagnosis text, the sub-view projection layer is used for determining the sub-view classificationprobability of the corresponding primary diagnosis text for each international disease classification ICD based on the primary diagnosis semantic vector; and taking the m sub-items with the highest classification probability for the main diagnosis text as recommended main diagnosis ICD sub-items of the main diagnosis text. According to the invention, corresponding ICD codes can be intelligently and automatically recommended based on texts, and the accuracy and the efficiency are high.

The invention, which belongs to the technical field of the fault diagnosis of the thermodynamic system, discloses a fuzzy nearest neighbor fusion diagnosis method of a thermodynamic system fault. A feature parameter of a thermodynamic system fault is obtained when a set works on a rated condition and a normal value of the feature parameter on the rated condition is determined; standardization processing is carried out on the feature parameter by using a symptom calculation method and a typical fault prototype is obtained by using a gravitation searching algorithm; according to a measured value and the normal value of the feature parameter, a real-time fault symptom is calculated; similarity between the real-time fault symptom and the typical fault prototype is compared and a fuzzy nearest neighbor classifier provides a fault membership; on the basis of combination with the fault membership provided by the fuzzy nearest neighbor classifier, a neural network carries out secondary diagnosis to obtain a final diagnosis result. The method has advantages of fast diagnosis speed and high diagnosis precision and can be used for diagnosis of a thermodynamic system fault on a rated condition or different steady-state conditions; and with real-time prediction of the fault feature parameter, the method is also suitable for the thermodynamic system fault diagnosis during the variable-condition dynamic process.

The invention discloses a medicine taking and diagnosis attendance reminding method and device and a terminal with a medicine taking and diagnosis attendance reminding function. The method comprises the steps that basic information and outpatient prescription information of a patient are acquired; according to the basic information and the outpatient prescription information of the patient, the medicine taking time and medicine taking dose of the patient and matters needing attention during medicine taking are acquired; according to the medicine taking time and dose of the patient and the matters needing attention during medicine taking, the patient is reminded to take medicine, and the medicine taking condition of the patient is recorded; according to the medicine taking condition of thepatient, secondary diagnosis attendance time of the patient is calculated, and the patient is reminded of diagnosis attendance and appointment register. According to the method, the patient can be reminded to take medicine according to the schedule and dose in time, and a user is automatically reminded of secondary diagnosis attendance in time and automatic appointment register.

The invention relates to a diagnosis method of first-aid handheld diagnosis equipment with an X-ray testing function. The method comprises the steps of determining a second clause in a predicting listand instructing the handheld diagnosis equipment to execute a specific event for generating at least one second medical image when a first medical image is received; when a binding relation between amedical image analysis result and a bone fracture risk evaluated value at a second time point satisfies a preset relation determining condition, outputting a corresponding preliminary diagnosis result in the predicting list to the handheld diagnosis equipment and a medical service platform; and performing feedback of comprehensive information which at least comprises the preliminary diagnosis result to a doctor for performing secondary diagnosis and obtaining an accepting result to the preliminary diagnosis result and a secondary diagnosis result. The diagnosis method based on the database can determine whether a high risk degree exists in different conditions, thereby supplying effective guidance support for adapting with a changeable outdoor environment and the patients with different physiques.

The invention discloses an intelligent appointment doctor seeing method for outpatient patients, which is used for improving appointment doctor seeing efficiency and enabling medical resources to be reasonably allocated. The method comprises the following steps: S1, a pre-diagnosis module judges symptoms according to the condition of a patient to form first data, and performs doctor-patient matching according to the first data to obtain a pre-diagnosis module, so that the patient can select a matched hospital; S2, the in-diagnosis module judges whether the current patient is subjected to primary diagnosis or secondary diagnosis through auxiliary diagnosis, and corresponding diagnosis and treatment are carried out. According to the intelligent appointment doctor seeing method for the outpatient, the online and offline doctor seeing modes can be appointment for the patient, and the first diagnosis and the second diagnosis of the patient are effectively distinguished, so that the doctor seeing of the patient is more targeted, the efficiency is improved, and the doctor seeing pressure of offline doctors is relieved.

The invention provides a medical service providing system and method, and the system comprises at least one local inspection device which is used for a local doctor to inspect a patient to obtain an inspection result containing a device code; at least one local doctor terminal which is used for inputting basic information of a patient by a local doctor and generating and uploading a local examination sheet according to the basic information and an examination result when the equipment code is in a preset code library; a service providing end which is used for issuing a diagnosis request of a local checklist for each remote doctor end to preempt and obtain a doctor diagnosis result, judging whether a pre-diagnosis result obtained through processing according to the artificial intelligence model accords with a doctor diagnosis result or not: if yes, the doctor diagnosis result is output, and if not, a confirmation signal is given, and taking a secondary diagnosis result as the doctor diagnosis result to be output, and generating an examination report according to the doctor diagnosis result. The invention has the beneficial effects that a service mode of local examination and unlimited regional diagnosis is provided, and patients can enjoy medical services of level hospitals locally.

The invention provides a computer technology based misalignment fault diagnosis method for a shaft coupling of a blower fan. The method comprises the following steps of S101) data collection and preprocessing, S201) primary diagnosis, S301) secondary diagnosis and S401) final diagnosis; and the four steps are used to diagnose a misalignment fault of the shaft coupling of the blower fan. The invention also provides a computer technology based misalignment fault diagnosis device for the shaft coupling of the blower fan. The device comprises an encoder, a data collection module, a preprocessing module, a figure generation module, a fault diagnosis module and a device control module. The device and method can be used to diagnose the misalignment fault of the shaft coupling of the blower fan in real time; an algorithm is optimized, the misalignment fault of the shaft coupling of the blower fan is diagnosed in three levels, the efficiency and accuracy of fault diagnosis are improved, and a threshold is adjusted so that the method and device are suitable for different types of blower-fan coupling shafts.

The invention solves the technical problem of providing a full diagnosis system and method for states of instrument control system Level 2 redundant devices of a nuclear power plant, particularly the diagnosis method for the states after the redundant network devices unsatisfying single faults are crossed and broken. The fault diagnosis device, system and method for the Level 2 redundant devices of the nuclear power plant comprise a diagnosis server side and a diagnosis client side. The diagnosis server side comprises a host diagnosis server side and a slave diagnosis server side. The diagnosis server side comprises a diagnosis client side request processing module, a diagnosis client side request forwarding module, a module for updating device diagnosis states to a real-time database, and master and secondary diagnosis server side data alignment modules. The diagnosis client side comprises a local device state diagnosis module.

A deep learning-based head and neck squamous cell carcinoma lymph node metastatic carcinoma diagnosis auxiliary identification system comprises an image scanning import subsystem, an image identification and evaluation subsystem, a diagnosis auxiliary model autonomous correction subsystem and a result output module. The image identification and evaluation subsystem comprises a tissue region identification model and a metastatic cancer region discrimination model; the tissue region identification model is used for removing a background region of an image by using an image segmentation algorithm to obtain a tissue region; and the metastatic cancer area discrimination model is used for performing segmentation diagnosis on a tissue area by using a secondary diagnosis model constructed based on a deep learning algorithm, and performing labeled diagnosis on the overall potential cancer focus area of a lymph node in a result output module. According to the invention, a secondary diagnosis model is constructed through the deep learning algorithm to identify a lymph node full slice, the possible cancer focus area is screened out, the film reading time of pathologists is reduced, the diagnosis efficiency is improved, and the diagnosis model also has autonomous correction and updating capabilities.

The invention belongs to the field of genetic engineering and oncology, and discloses a low-frequency high-penetrance genetic marker associated with the auxiliary diagnosis of primary lung carcinoma and applications of the marker. The marker is a combination of 35 genetic loci such as rs1131897, rs1133833, rs115019901, rs117855259, rs118154190, rs141059768, rs141350740, rs142881943, rs145529151, rs145638335, rs145940981, rs150279473, rs150695913, rs151223396, rs185832840 and rs188159138. The marker can be used for preparing kits for the auxiliary diagnosis of primary lung carcinoma.

The invention provides a breast ultrasound image quality evaluation method based on auxiliary diagnosis and subjective aesthetics. Firstly, construct an ultrasound image database with a small amount of strong-supervised annotation information and a large amount of weak-supervised annotation information; then, adopt a variety of small-sample learning strategies to train the deep network model DNN-1 for automatic segmentation of lesion ROI; then, combine the ROI image with the original image Input together, and train to obtain the ultrasound-assisted diagnosis network DNN-2; finally, transfer the convolutional layer of the auxiliary diagnosis network, combined with the doctor's aesthetic score, train the aesthetic evaluation convolutional neural network DNN-3, and combine DNN-2 based on the attention mechanism , to obtain the breast ultrasound image quality evaluation results.

The invention relates to the technical field of medical management, and discloses a medical management method and system, so as to improve the medical efficiency in a process reconstruction mode. The method comprises the following steps of: setting a primary diagnosis and treatment sheet and a secondary diagnosis and treatment sheet which have an association relationship with an initial same first effective duration; generating a first type of two-dimensional code information for the user to scan the code for payment in the sub diagnosis and treatment sheet, and setting a second effective duration of the diagnosis and treatment result collected by the sub diagnosis and treatment sheet; judging whether the deadline of the second effective duration is later than or equal to the deadline of the first effective duration according to the generation time of the diagnosis and treatment result collected by the sub-diagnosis and treatment list; if not, setting the first type of two-dimensional code information corresponding to the diagnosis and treatment sub-sheet to be in a reactivated state in which at least part of information of the diagnosis and treatment sub-sheet can be copied from the deadline corresponding to the second effective duration to the deadline corresponding to the first effective duration; and in a time period corresponding to the reactivation state, generating a new sub diagnosis and treatment sheet cascaded with the sub diagnosis and treatment sheet to guide the operation user to confirm and pay.

The invention discloses a fuzzy nearest neighbor fusion diagnosis method for thermal system faults, which belongs to the technical field of thermal system fault diagnosis. Obtain the characteristic parameters of the thermal system faults under the rated working conditions of the unit, and determine the normal values ​​of the characteristic parameters under the rated working conditions; use the symptom calculation method to standardize the characteristic parameters, and use the gravity search algorithm to obtain typical fault prototypes; according to the characteristic parameters The real-time fault symptoms are calculated by the measured value and the normal value; the similarity between the real-time fault symptoms and the typical fault prototype is compared, and the fault membership degree is given by the fuzzy nearest neighbor classifier; Diagnosis, give the final diagnosis result. It has the advantages of fast diagnosis speed and high diagnostic accuracy; it can be used for thermal system fault diagnosis under rated working conditions and different steady-state working conditions; through real-time prediction of fault characteristic parameters, it can be applied to dynamic process thermal system fault diagnosis under variable working conditions .

The invention provides a method for diagnosing and locating an open circuit fault of a switch tube of a single-phase three-level rectifier of a high-speed rail traction system, belonging to the field of fault diagnosis. The method includes the following steps: establishing a hybrid logic dynamic model, establishing a new adaptive sliding mode observer, proposing an adaptive threshold for primary diagnosis, primary fault diagnosis, proposing an adaptive threshold for secondary diagnosis, diagnosing and locating secondary faults, and proposing tertiary diagnosis Adaptive threshold, three fault diagnosis and localization. The adaptive sliding mode observer proposed by the present invention does not require the system to provide a very accurate dynamic model, but only needs to use the tracking error of the trajectory to reasonably design the sliding mode surface, and can adaptively switch the approach rate, thereby speeding up the approach speed. And the chattering of the sliding mode motion is reduced, and the accuracy of diagnosis is improved; the method can diagnose and locate the fault of the switch tube by comparing the relationship between the residual feature quantity and the adaptive threshold.