48 results about "The primary diagnosis" patented technology

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.

A method and chart for alerting a medical caregiver to undetected or developing complications associated with, or resulting from, initially diagnosed or suspected medical problems. First, a list is prepared of possible complications that might occur based upon the initial diagnosis. Signs of the complications are concisely listed on the chart. The concise chart is posted at, or is otherwise available or near the patient's location, such as at a hospital bed or nurse's station, or other easily observable locations. Thereafter, various caregiver personnel who attend to, or routinely visit, the patient for performing various services, routinely check the listed signs against the patient's condition when the patient is visited. Each caregiver person records the presence of, and any observed changes in, the listed signs that are observed giving the time of the observation. Lastly, an appropriate caregiver physician is alerted to the noted signs for diagnosing and prescribing appropriate treatments. These complications which are present or are developing in the patient can be recognized quickly and appropriate treatment may be undertaken immediately when needed.

The invention discloses a comprehensive analysis method of multi-dimensional biology opto-acoustic image spectra. The method comprises steps as follows: establishing a disease sample library of certain biological tissue; illuminating a certain sample with laser having a certain wavelength to produce an optoacoustic effect, and collecting a two-dimension opto-acoustic image of the sample; performing two-dimension Fourier transform on the image, obtaining two-dimension opto-acoustic spectrograms, and extracting characteristic spectra of the two-dimension opto-acoustic spectrograms; continuously changing the wavelength of the illuminated laser, and combining a plurality of groups of two-dimension opto-acoustic spectrograms and characteristic spectra into three-dimension opto-acoustic spectrograms and three-dimension characteristic spectra according to different wavelengths; establishing a three-dimension opto-acoustic spectrogram library of all samples of the biological tissue; and acquiring three-dimension opto-acoustic spectrograms of to-be-diagnosed tissue, comparing and matching spectrogram data in the library, and obtaining a primary diagnosis result. According to the method, with the adoption of the optoacoustic effect of the tissue and through analysis of the three-dimension opto-acoustic spectrograms of the to-be-diagnosed tissue, disease conditions are judged in two aspects of a spatial domain and a frequency domain, so that the accuracy of the primary diagnosis is effectively improved.

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 discloses a sleep snore monitoring method and system based on the bass ratio. The method includes the following steps of recording sleep snores of a patient at the whole night, extracting each sleep snore signal in the record, conducting octave frequency band filtering on each sleep snore signal, obtaining multiple levels of octave frequency band sound pressure or multiple sound pressure level values of each sleep snore signal so as to obtain the bass ratio of each sleep snore, and monitoring the sleep snores at the whole night according to the bass ratio of each sleep snore. According to the method and the system, by calculating the bass ratio of the sleep snores of the patient, whether the snores of the patient are normal snores or abnormal snores is judged, the serious degree of the obstructive sleep apnea-hypopnea syndrome (OSAHS) is judged, and the primary diagnosis is provided for the patient; meanwhile, the selectable method is provided for the subjective evaluation on the post-operation effect.

The invention discloses a fault diagnosis system based on the evidence theory, and the system comprises a sensor acquisition module, a data preprocessing module, a primary diagnosis module, a comprehensive diagnosis module and a result display module. The sensor acquisition module collects data of transformer parameters through a plurality of sensors. The data preprocessing module is used for carrying out the preprocessing of the data, and the primary diagnosis module is used for carrying out the primary diagnosis of a device according to the preprocessed sensor data. The comprehensive diagnosis module uses the evidence theory to carry out the comprehensive diagnosis of the device according to the primary diagnosis result. The result display module uses an LED display to display the faultdiagnosis result in real time, and performs early warning when the device is diagnosed to have a fault. The beneficial effects of the invention are that the system employs the neural network for processing the sensor data after fuzzification to obtain a primary diagnosis result of transformer fault; the system employs the evidence theory for further diagnosing the transformer fault according to the primary diagnosis result, thereby improving the accuracy of the diagnosis result.

The invention discloses an SF6 device secondary fault diagnosis method based on mass data parallel computation. According to the corresponding relationship between the SF6 decomposed gas component content and the fault type in an electrical device, firstly, a secondary fault diagnosis model of an SF6 electrical device is parallelly constructed, and the modeling efficiency is improved. Then parallel diagnosis of the SF6 electrical device is achieved, the diagnosis rapidity and accuracy in a big data environment are improved. The parallel diagnosis process of the SF6 device secondary fault diagnosis method is that each lab diagnoses different pieces of data at the same time, specifically, a decision tree model is employed to carry out primary diagnosis on the pieces of data and determine whether the device has a fault, and therefore the mass data processing speed is increased. For fault data, the fault type is accurately determined through a neural network model. By employing the SF6 device secondary fault diagnosis method, the diagnosis result can be obtained only through simple data processing, the demand on the professional skill of an operator is greatly reduced, when a lot of SF6 electrical devices are diagnosed, the diagnosis efficiency is greatly improved.

This invention is directed to embodiments of systems and methods to identify a subgroup of ADHD at higher risk for complicating conditions that, for example, may be of concern to an ADHD evaluation, may account for attention and behavior symptoms, and may lead a clinician to exclusion of ADHD from primary diagnosis. In one embodiment, a method for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at higher risk for complicating conditions is provided. The method can include receiving, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; obtaining EEG data for each of the plurality of patients; determining, based at least in part on the EEG data, an indicator of ADHD, wherein the indicator supports a positive or negative ADHD evaluation; correlating the indicator with a user's or clinician's evaluation data; and based at least in part on the correlation, determining at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support for further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup.

The embodiment of the invention provides a system and method for monitoring an emergency ambulance. The system comprises a monitoring terminal and a monitoring device. The monitoring terminal is used for receiving the primary diagnosis result of an emergency patient on the emergency ambulance and sending the primary diagnosis result to a monitoring server; the monitoring device is used for monitoring the emergency ambulance and sending the monitoring result to the monitoring server; the monitoring server comprises a diagnosis result receiving module, a monitoring task creating module, an execution flow path return module and a monitoring module; the diagnosis result receiving module is used for receiving the primary diagnosis result sent by the monitoring terminal; the monitoring task creating module is used for creating monitoring tasks for the emergency ambulance; the execution flow path return module is used for extracting execution flow paths of the emergency ambulance corresponding to the primary diagnosis result to return to the emergency ambulance; the monitoring module is used for executing the monitoring tasks and judging whether the emergency ambulance executes the execution flow paths or not according to the monitoring result returned by the monitoring device.

The embodiment of the present invention provides a system and method for monitoring an ambulance. The system includes: a monitoring terminal, used to receive the preliminary diagnosis result of the emergency patient on the ambulance, and send the preliminary diagnosis result to the monitoring server; a monitoring device, used to monitor the ambulance, and send the monitoring result to the monitoring server. sent to the monitoring server; the monitoring server includes a diagnosis result receiving module, a monitoring task creation module, an execution process return module and a monitoring module; a diagnosis result receiving module, used to receive the preliminary diagnosis result sent by the monitoring terminal; a monitoring task creation module, used To create a monitoring task for the ambulance; the execution flow return module is used to extract the execution flow of the ambulance corresponding to the preliminary diagnosis result and return it to the ambulance; the monitoring module is used to execute the monitoring task, according to the The monitoring result returned by the monitoring device determines whether the ambulance executes the execution procedure.

The invention relates to an improved D-S evidence theory-based lithium battery fault diagnosis method, which is used for determining the state of a lithium battery. The method comprises the following steps: primarily diagnosing the fault of the lithium battery by utilizing at least two diagnosis methods; according to the primary diagnosis results, constructing the evidence body corresponding to each diagnosis method, and calculating the elementary probability distribution function of each evidence body; based on the elementary probability distribution function of each evidence body, correcting the weight of each evidence body to obtain weighed evidence body; calculating the confidence degree of each nominalized focal element, obtaining a combination rule according to the confidence degree, and fusing the evidence body and the weighed evidence body corresponding to the diagnosis method according to the combination rule, to obtain the fused diagnosis result; and according to the fused diagnosis result, determining the state of the lithium battery by applying a decision rule. Compared with the prior art, the improved D-S evidence theory-based lithium battery fault diagnosis method has the advantages of being accurate in diagnosis results, high in evidence utilization rate, high in diagnosis precision, and the like.

Deep RNA sequencing is a technology that provides an initial diagnostic for sepsis that can also monitor the indicia of treatment and recovery (bacterial counts reduce, physiology returns to steady-state). The invention can be used for many other hospital conditions, particularly those needing an intensive care unit stay with the attendant risk of bacterial infection, such as trauma, stroke, myocardial infarction, or major surgery.