60results about How to "Fast and accurate diagnosis" patented technology

Disclosed is a method, system, program, and data structure for maintaining electronic patient medical information. An electronic patient data structure is generated to include patient biographical information and one of medical history information, medication schedule information, and appointment schedule information. The patient data structure is electronically transmitted between a physician computer and a portable patient device. The patient data structure is capable of being modified.

The invention discloses a clustering analysis-based intelligent fault diagnosis method for an antifriction bearing of a mechanical system. A diagnosis model is trained firstly, comprising the following steps: collecting standard vibration signal samples of five fault and normal bearing states of an outer ring, an inner ring, a rolling body and a holding frame; decomposing signals, extracting original vibration signals as well as time domain and frequency domain characteristics of decomposed components to obtain an original characteristic set; removing redundancy by means of a self-weight algorithm and an AP (Affinity Propagation) clustering algorithm to obtain Z optimal characteristics; classifying sample statuses by means of the AP clustering algorithm to obtain a well-trained diagnosis model. A fault diagnosis is performed by the following steps: collecting real-time vibration information of a bearing, decomposing the signals, extracting the optimal characteristics determined by the model, importing the AP clustering algorithm to cluster parameters based on the diagnosis model, comparing with the Z characteristics known in the model to obtain a category of a current unknown signal, so as to complete the fault diagnosis. According to the clustering analysis-based intelligent fault diagnosis method disclosed by the invention, both EEMD (Ensemble Empirical Mode Decomposition) and WPT are utilized to decompose the vibration signals, more refined bearing status information can be acquired, the self-weight algorithm and the AP clustering algorithm increase intelligence of the diagnosis, and therefore accurate diagnosis is ensured.

The invention discloses a colposcopy image-based cervical cancer detection method, device and terminal equipment and a computer readable storage medium. The method comprises the following steps of: ina bidirectional convolutional neural network-based cervical cancer detection model, positioning and extracting a cervical opening position of an obtained colposcopy image so as to generate an ROI image comprising a cervical cancer disease area; extracting a cutting edge of the ROI image through a bidirectional convolutional neural network so as to generate a cut image; and carrying out cancer grade classification on the cut image through a classification convolutional neural network so as to output a cervical cancer lesion grade and then rapidly and correctly obtain a cervical cancer detection result. According to the method, doctors that are lack of experiences can be helped to rapidly judge diseased regions, discover atypical diseased regions and judge the disease degrees and sampling regions, so that help and auxo-action are provided for discovering cervical cancer and precancerous lesions.

The invention discloses a fault monitoring early-warning system and method of a shield machine. The system comprises a host monitor, a shield machine condition detector for monitoring condition information of a monitored shield machine in real time, an early warning prompt device controlled by the host monitor, and a timing circuit connected with the host monitor; the early warning prompt device is connected with the host monitor; and the shield machine condition detector comprises a main bearing condition detection unit which monitors the condition of a main bearing of the shield machine in real time, a cutterhead detection unit which monitors the condition of a cutterhead of the shield machine in real time, and a cutterhead driving detection unit for monitoring the condition of a cutterhead driving system in real time. The method comprises the steps that 1) the condition of the shield machine is monitored, and monitoring information is uploaded synchronously; and 2) condition information of the shield machine is analyzed and processed. Thus, a fault in the shield machine can be monitored timely and accurately, and early warning prompt can be provided according to a monitoring result.

The invention discloses a transformer fault diagnosis method, and the method comprises the steps: step1, a vibration signal of a transformer is acquired, and noise reduction preprocessing is performed on the vibration signal; step2, EMD decomposition is performed, obtained IMF components are selected according to set critical values, so that the IMF components with low amplitude are removed can be prevented; step3, wavelet analysis is performed, and feature vectors after de-noising are obtained; step4, a three layers BP neural system is constructed, feature vectors extracted from the wavelet analysis serves as input vectors of BP neural network training to train, and a fault signal is outputted. According to the invention, methods such as the wavelet analysis and the like are adopted to remove interference signal in the fault signal, transformer internal fault occurrence and development multi-process and multi-fault multiple modes are diagnosed through the neural network, the transformer fault can be quickly and accurately diagnosed, the fault diagnosis efficiency is improved, the service life of the transformer is prolonged, the unnecessary costs is reduced, and the cost is saved.

The invention discloses a turbo generator set vibration fault diagnosis method based on forward reasoning. After a diagnosed turbo generator set starts, a parameter detection device is employed to carry out real-time detection on related work parameters in a start and operation process of the diagnosed turbo generator set and synchronously sends the detection information to a vibration fault diagnosis device for automatic vibration fault diagnosis, vibration faults of the diagnosed turbo generator set are diagnosed level by level by the vibration fault diagnosis device according to the detection result transmitted by the parameter detection device in combination with the active power value of the diagnosed turbo generator set, and the fault diagnosis process comprises steps of 1, shaft vibration swinging value diagnosis; 2, start process vibration fault diagnosis; 3, zero load operation vibration fault diagnosis; and 4, loaded operation vibration fault diagnosis. The method is advantaged in that the steps are simple, and the method is reasonable in design, is convenient to realize, has good use effects, can conveniently and rapidly accomplish the online steam turbine vibration fault diagnosis process and can further realize accurate and reliable diagnosis results.

The invention relates to pulse signal processing for pulse diagnosis in traditional Chinese medicine (TCM). A TCM pulse diagnosis device according to the invention comprises an input unit, a processing unit and a display terminal, wherein the input unit is used for receiving user input; the processing unit is used for determining the state of pulse condition elements according to characteristic parameters of a pulse waveform of an examined object; and a display screen of the display terminal consists of a first region for displaying the pulse waveform of the examined object, and a second region for displaying the state of the group of pulse condition elements of the examined object. By means of displaying the waveform of pulse signals and the state of the pulse condition elements on the display screen at the same time, a professional can acquire firsthand information of the pulse signals simply and clearly. In addition, the provided season and time when the pulse signals are acquired ensure that the professional can make a more complete diagnosis result. Furthermore, by means of mapping the characteristic parameters of the pulse signals, of which the values are obtained continuously, into the discrete state of the pulse condition elements, a transformed signal processing result is in better conformity with the thinking mode of the TCM diagnosis, so that the usage of the professional is facilitated.

The invention discloses a method for identifying a rail corrugation damage based on a vehicle body acceleration. The method comprises the following steps of (S1) obtaining vehicle body vibration acceleration data in a train running process; (S2) obtaining vehicle body vibration acceleration data between two adjacent stations; (S3) obtaining a main frequency of vehicle body vibration; (S4) obtaining a peak frequency in rail corrugation according to the main frequency of vehicle body vibration; (S5) obtaining speed information and mileage information of a train; and (S6) obtaining a corrugationwavelength according to the speed information of the train and the peak frequency in rail corrugation, obtaining the specific position according to the mileage information and completing identification of the rail corrugation damage. According to the method, carriage floor vibration is measured based on an acceleration sensor, and the rail corrugation can be economically, conveniently, quickly andaccurately diagnosed according to the running speed and the mileage information of the train, thereby providing an important data support for a subway operation company for developing a scientific and efficient maintenance strategy.

The invention discloses a fully mechanized coal mining face coal cutter automatic height-adjustment control method based on current monitoring. The fully mechanized coal mining face coal cutter automatic height-adjustment control method based on current monitoring includes the steps that firstly, a coal cutter mining work condition monitoring system is built, specifically, the built coal cutter mining work condition monitoring system comprises a sound intensity detection device, a lower monitoring device installed on a coal cutter and an upper monitoring machine arranged in an upper monitoring room; and secondly, automatic height-adjustment control over the coal cutter is carried out, specifically, the coal cutter is used for mining a coal seam to be mined in the work face advancing direction from back to front; and when any mining position of a current work face is mined, the coal cutter mining work condition monitoring system is used for carrying out coal cutter automatic height-adjustment control, and the process is as follows: information detection and synchronous unloading of cutting current, traction current and sound intensity of the coal cutter, cutting work condition diagnosis, coal cutter height-adjustment judgment and cutting height adjustment of the coal cutter. The fully mechanized coal mining face coal cutter automatic height-adjustment control method based on current monitoring is simple in step, reasonable in design, easy and convenient to realize, good in use effect and capable of carrying out accurate control over coal cutter height adjustment automatically in real time.

The present invention describes a way to quantify the trapped-air disease and how to allow efficient user interaction for inspection via a graphical user interface. The results of the invention may also be used for rapid and accurate diagnosis of trapped air disease. An apparatus, graphical user interface, computer-readable medium and use are also provided.

The invention discloses a coal cutter height-adjustment remote control method based on virtual reality. The coal cutter height-adjustment remote control method based on virtual reality includes the steps that firstly, a coal cutter mining work condition monitoring system is built, specifically, the built coal cutter mining work condition monitoring system comprises a sound intensity detection device, a lower monitoring device and an upper monitoring machine; secondly, a three-dimensional model is built; and thirdly, synchronous simulation of coal seam mining and the mining process is carried out, specifically, a coal cutter is used for mining a coal seam to be mined in the work face advancing direction from back to front; and when any mining position of a current work face is mined, the process is as follows: information detection and synchronous unloading of actual mining work conditions of the coal cutter, cutting work condition diagnosis, coal cutter height-adjustment judgment, cutting height adjustment of the coal cutter and synchronous simulation of the mining work conditions of the coal cutter. The coal cutter height-adjustment remote control method based on virtual reality is simple in step, reasonable in design, easy and convenient to realize, good in use effect and capable of carrying out remote control over coal cutter height adjustment automatically in real time and synchronous simulation of the mining work conditions of the coal cutter.

The present invention provides a catheter for use in delivering and / or recovering materials to and / or from a tissue site in the body, the catheter comprising one or more macroporous regions adapted to selectively deliver molecules and / or recover cells from the tissue site, based on one or more physical-chemical-biological characteristics. The macroporous region can be provided in the form of a helical hollow wires, and can be adapted to both recover cells from the tissue site (e.g., bacterial or other cells present in interstitial fluid) and optionally to permit the infusion of medicament to the site, under corresponding conditions.

The invention relates to a pathological image processing system. The pathological image processing system comprises a microscope, a microscope camera, an acquisition switch, a processor and a display,wherein the microscope is used for observing the cell smear; the microscope camera is connected with the microscope lens and is used for collecting pathological images of the cell smear under the microscope; the processor is in communication connection with the microscope camera, receives a pathological image from a microscope camera, preprocesses the pathological image, carries out cell detection and cell classification on the processed pathological image, marks a cell position, a cell type and a corresponding confidence coefficient on the pathological image, and outputs the marked pathological image; the display is connected with the processor and is used for receiving and displaying the marked pathological image; and the acquisition switch is arranged on the microscope camera and controls the operation of the microscope camera.

The invention discloses a bearing-less motor suspension winding fault detection method. According to the method, two-phase suspension currents iSalpha and iSbeta acquired through respective sampling are taken as a pixel point of a binary image, and the pixel point is displayed under a static coordinate system; a binary image of a suspension winding having no fault is acquired through sampling, a circle O1 passing the most pixel points is taken from the binary image, and a radius R1 of the circle O1 is solved; the two-phase suspension currents iSalpha and iSbeta are sampled in real time at each time interval to acquire binary images in operation, a locus passing the most pixel points is taken from the binary images, if the locus is an ellipse, a long-axis radius R2 of the ellipse is solved; if the locus is a circle, a radius R2 of the circle is solved. The method is advantaged in that the current is represented in the image, fault-or-not generation conditions and a fault severity degree are determined according to the shape of the image, the method is simple to realize, and the fault can be rapidly and accurately diagnosed and corrected.

The present invention relates to the field of biomarkers. More specifically, the present invention relates to biomarkers useful in diagnosing brain injury or neurodegeneration. In one embodiment, a method for diagnosing brain injury in a patient comprises the steps of (a) obtaining a sample from the patient; (b) determining the ratio of citrullinated to unmodified arginine residues at one or more arginine residues of one or more brain injury biomarker proteins; and (c) correlating the ratio to a patient having brain injury or to a patient not having brain injury, thereby providing the diagnosis.

The invention discloses a state monitoring and defect simulation system for the electrical insulation performance of an oil-immersed bushing, and the system comprises an oil pressure monitoring modulewhich is used for monitoring the pressure of insulating oil in the oil-immersed bushing; a vibration characteristic monitoring module which is used for monitoring the vibration frequency and amplitude of the oil-immersed sleeve in the operation process; a discharge characteristic monitoring module which is used for judging whether the oil-immersed bushing is in a normal operation state or not bytesting the magnitude of partial discharge pulse current at the end part of the oil-immersed bushing and a discharge spectrum; a discharge phenomenon observation module which is used for observing theposition of a discharge point in the oil-immersed bushing and recording a discharge process image and animation at the discharge moment; and a dielectric response test module which is used for evaluating the insulation condition of the insulation material or the insulation equipment by changing the frequency of the alternating current excitation, taking complex capacitance and dielectric loss asfunctions of the frequency and using the change condition of the functions. According to the invention, comprehensive monitoring and analysis of electrical and mechanical property characteristic parameters can be carried out on defects.

The invention provides a medical image processing method and device, equipment and a storage medium. The medical image processing method comprises the steps of obtaining a to-be-classified medical image; performing feature extraction on the medical image according to a feature extraction network in the image classification model to obtain a feature image; and classifying the feature images according to a classification network in the image classification model to obtain category information of the feature images. According to the embodiment of the invention, the method can achieve the more accurate prediction of the types of to-be-classified medical images, and the prediction result can be used for assisting a doctor in the accurate and quick diagnosis of a disease of a patient, thereby improving the auxiliary diagnosis effect.

According to the invention, records pertaining to an individual are centralized such that the user has control over the integration and dissemination of their personal and private information. Records pertaining to an individual are systematically transported electronically by many different institutions to a centralized record storage provider wherein the individual user has ownership of and control of their confidential personal information. The systematic accumulation of medical records provides for better overall health tracking and faster and more accurate diagnosis when illness or emergency occurs.

A method of analysing a sample including a microorganism of interest. The method includes exposing the sample to an antimicrobial; after exposing the sample to the antimicrobial, applying an absorption-based and / or scattering-based spectroscopic technique to the sample to obtain spectrum data whose spectral profile has been influenced by exposing the sample to the antimicrobial, wherein applying the absorption-based and / or scattering-based spectroscopic technique to the sample includes irradiating the sample with UV-Vis radiation; obtaining information regarding the susceptibility / resistance of the microorganism of interest to the antimicrobial from the spectrum data. The absorption-based and / or scattering-based spectroscopic technique may be applied to the sample no more than 60 minutes after the initial exposure of the sample to the antimicrobial. The method may be useful to obtain information regarding the susceptibility / resistance of a bacterium, such as a bacterium responsible for causing a UTI, to an antibiotic in a rapid and reliable manner.

The invention discloses diagnostic equipment for suspected tuberculosis. The diagnostic equipment comprises a control device and an input device, an output device and a power supply device which are connected with the control device in series respectively, wherein the control device is an STC12C5A60S2 series singlechip microcomputer, the input device is a keyboard and a PC interface circuit, and the output device is a speech output device; and by the image processing method, the image information is divided into three categories, totally eight types of characteristics, a value corresponding to each type of characteristics is set, the values corresponding to the three categories of characteristics are summed to give a result value, the result value is divided into three value intervals, and one image processing result corresponding to each interval is outputted. When the diagnostic equipment is used for non-professional tuberculosis prevention and control organizations, a finding rate of patients suffering tuberculosis is improved, the spread of tuberculosis among people is avoided, a misdiagnosis rate and a rate of missed diagnosis are both greatly lowered, the work load of medical staff in the X-ray department, the working efficiency is improved, and the information on the medical staff making the diagnosis is also recorded in order to apply a responsibility system and strengthening the sense of responsibility of the medical staff.

The invention discloses a method for typing chronic nasosinusitis based on a digital pathological slide. The method comprises the following steps: acquiring an image, namely acquiring a digital pathological image from the chronic nasosinusitis nasal polyp slide, and sketching to generate a large mask image; preprocessing the image to obtain a small pathological image and a small mask image; establishing training set data; establishing a deep learning quantitative prediction module; training on an ImageNet data set by adopting an Inception V3 model to obtain model parameters; removing the lastfull-connection layer FC of the model, adding a full-connection layer FC, only one neuron being arranged in the full-connection layer FC, not using activation function, setting a loss function to adopt a mean square error MSE, and setting a learning rate lr; integrating the eosinophilic granulocyte proportion values of all the small pathological pictures on the slide to obtain a final auxiliary diagnosis result. The invention also discloses a system thereof. According to the method, the eosinophilic granulocyte proportion on the pathological picture is rapidly obtained through learning and training, and an objective and high-accuracy auxiliary diagnosis result is given.

The invention discloses a dynamic fault detection method for an electro-hydraulic executer energy accumulator. The dynamic fault detection method comprises the following step that field input signalswhen an intelligent electro-hydraulic executing mechanism is in the work state are collected, and the field input signals include pressure sensor signals, displacement sensor signals, temperature sensor signals, liquid level sensors and motor state signals. The dynamic fault detection method has the beneficial effects that rapid and accurate detection and diagnosis can be conducted on all faults of an EHS intelligent electro-hydraulic executing control system, the automatic control system reliability analysis technology, the fault detection technology and the artificial intelligence knowledgereasoning judgment technology can be comprehensively applied to achieve the fault detection and diagnosis technology only owned by few talented persons originally, a user conveniently knows and graspsthe real-time health condition of the whole system running, and accordingly fault enlarging and disastrous events can be prevented.

A model-based method and system for diagnosing an open-circuit fault of a power transistor of a three-phase converter are provided, which belong to the technical field of fault diagnosis of power electronic equipment and can implement fast and accurate diagnosis of the open-circuit fault of the power transistor of the three-phase converter without adding an additional hardware. The fault diagnosis method of the disclosure only needs current and voltage sampling signals and drive signals that already exist in a control system of the converter and has the advantage of simple implementation. A cycle accumulated value of a difference between a sampling current and an estimated current after the power transistor of the converter has the open-circuit fault is used as a diagnostic variable, which can quickly and accurately complete diagnosis of a faulty power transistor and has relatively strong practicability.

The invention discloses a multiple-water-resource key-point damage control and safe water supply method, and belongs to the technical field of urban water supply. In order to guarantee safe operation of a water supply pipe network system and prevent unexpected accidents, a mode recognition function of a network is utilized, key control points determined in the HACCP analysis are combined, factors like water quality, the water volume and water pressure are considered comprehensively and a multiple-water-resource key-point damage control and safe water supply technology based on a mathematic damage control model of key nodes is built. The method has the advantages of being capable of mastering the operation condition of a water supply pipe network in real time, fast and accurately diagnosing prospective faults, feeding back alarm information and reducing risks probably generated in the water supply production, processing and conveying processes of small-town water supply.

The invention discloses a control method for the automatic height adjustment of coal cutter rollers. The method comprises the following steps: a front hydraulic lifting platform is arranged at the front part of a coal cutter body; a rear hydraulic lifting platform is arranged at the rear part of the coal cutter body; a front lifting oil cylinder is arranged below the front hydraulic lifting platform; a rear lifting oil cylinder is arranged below the rear hydraulic lifting platform; a first displacement detection unit is arranged on the front hydraulic lifting platform; a second displacement detection unit is arranged on the rear hydraulic lifting platform; a first height adjustment oil cylinder is arranged on a front swing arm; a rear height adjustment oil cylinder is arranged on a rear swing arm; a first height detection unit is arranged on a front cutting roller; and a second height detection unit is arranged on a rear cutting roller. The height adjustment control method has the advantages of reasonable design, simplicity, fastness and accuracy in the diagnosis of the cutting condition of coal cutters in various exploitation positions, realization of automatic real-time control of the height adjustment of the coal cutter by automatically adopting a corresponding height adjustment control scheme, and realization of remote monitoring of the coal cutter.

During operation, embodiments of the subject matter can perform compression of an n-dimensional m-channel patch based on unsupervised learning (clustering). Embodiments of the subject matter can perform multiple such compressions of patches tessellated (tiled) across a space. Embodiments of the subject matter can also perform hierarchical compression through recursive application of embodiments of the subject matter. Embodiments of the subject matter can compress but are not limited to compressing the following: a database, a sequence, an image, a video, and a volumetric video.

The present invention relates to a diagnostic method for Behcet's disease using metabolome analysis and provides a biomarker with which Behcet's disease can be effectively diagnosed using metablomics,and which can be applied to the development of a therapeutic agent for Behcet's disease.