557 results about "Severity/Intensity" patented technology

A system and method of obtaining serial biochemical, anatomical or physiological in vivo measurements of disease from one or more medical images of a patient before, during and after treatment, and measuring extent and severity of the disease is provided. First anatomical and functional image data sets are acquired, and form a first co-registered composite image data set. At least a volume of interest (ROI) within the first co-registered composite image data set is identified. The first co-registered composite image data set including the ROI is qualitatively and quantitatively analyzed to determine extent and severity of the disease. Second anatomical and functional image data sets are acquired, and form a second co-registered composite image data set. A global, rigid registration is performed on the first and second anatomical image data sets, such that the first and second functional image data sets are also globally registered. At least a ROI within the globally registered image data set using the identified ROI within the first co-registered composite image data set is identified. A local, non-rigid registration is performed on the ROI within the first co-registered composite image data set and the ROI within the globally registered image data set, thereby producing a first co-registered serial image data set. The first co-registered serial image data set including the ROIs is qualitatively and quantitatively analyzed to determine severity of the disease and/or response to treatment of the patient.

The present invention identifies biomarkers that are diagnostic of nerve cell injury, organ injury, and/or neuronal disorders. Detection of different biomarkers of the invention are also diagnostic of the degree of severity of nerve injury, the cell(s) involved in the injury, and the subcellular localization of the injury.

A computerized system and method for intuitively detecting a user's need for emergency help, preventive care and medical interventions and also for coordinating care for user's loved ones and pets when user experiences an emergency or has passed away. Detection is done via labs and life signs equipment and sensors, self-initiated request for monitoring or the system's periodically polling user through an alert, a telephone call, a notification, a text message or other appropriate means to find out if they are in danger. Polling and automated monitoring may also be triggered by real-time medical data electronically or wirelessly transmitted to the system. If user fails to respond, the system automatedly calls either user's contacts (by listed priority) to notify them of a potential emergency, or emergency responders directly depending on severity of the emergency and communicates to them critical information as well as a code to access user's medical record(s).

An error logging and analysis system is used to detect a type of error condition, assign a numeric value corresponding to the severity of the error condition, record the time of the error condition, and determine the frequency between subsequent error conditions of the same type. A weighted error rate is generated as a function of the severity of the initial error condition, the frequency of subsequent error conditions, and a percentage of any preceding weighted error rates. These weighted error rates are compared to a predetermined threshold to determine if the error condition is statistically significant.

An automated method for determining prognosis based on an analysis of abnormality (lesion) features and parenchymal features obtained from medical image data of a patient. The techniques include segmentation of lesions from radiographic images, extraction of lesion features, and a merging of the features (with and without clinical information) to yield as estimate of the prognosis for the specific case. An example is given for the prognosis of breast cancer lesions using mammographic data. A computerized image analysis system for assessing prognosis combines the computerized analysis of medical images of cancerous lesions with the training-based methods of assessing prognosis of a patient, using indicators such as lymph node involvement, presence of metastatic disease, local recurrence, and/or death. It is expected that use of such a system to assess the severity of the disease will aid in improved decision-making regarding treatment options.

A system and method for managing patient triage in an automated patient management system is presented. A criteria for placement of patient data into a display is defined for a plurality of remotely managed patients. The patient data originates from one or more patient data sources operating on each such patient and selected from at least one of a physiological sensor and a therapy delivery device. An ordering of the patient data within the display is defined based on a need of care in relation to one or more of a type of health condition, severity of the health condition, and facilities available to attend to the health condition. An organization of the patient data within the display is defined in relation to metadata associated with the patient data.

A system and methods of diagnosing and monitoring neurological disorders in a patient utilizing an artificial intelligence based system. The system may comprise a plurality of sensors, a collection of trained machine learning based diagnostic and monitoring tools, and an output device. The plurality of sensors may collect data relevant to neurological disorders. The trained diagnostic tool will learn to use the sensor data to assign risk assessments for various neurological disorders. The trained monitoring tool will track the development of a disorder over time and may be used to recommend or modify the administration of relevant treatments. The goal of the system is to render an accurate evaluation of the presence and severity of neurological disorders in a patient without requiring input from an expertly trained neurologist.

This invention relates to one gas wheel motor rotor coil shortcut online test method in the test technique field, which comprises the following steps: through online real time collecting motor electrical parameter data and according to one certain work situation motor electrical parameter data to compute normal current theory values by reverse rotor normal current; then computing excitation magnetic current real value and theory value relative bias; the bias difference is as generation motor set to judge whether there is coil short cut fault as dialogue of the shortcut fault.

Techniques are provided for detecting and evaluating ventricular dyssynchrony based on morphological features of the T-wave and for controlling therapy in response thereto. For example, the number of peaks in the T-wave, the area under the peaks, the number of points of inflection, and the slope of the T-wave can be used to detect ventricular dyssynchrony and evaluate its severity. As ventricular dyssynchrony often arises due to heart failure, the degree of dyssynchrony may also be used as a proxy for tracking the progression of heart failure. Pacing therapy is automatically and adaptively adjusted based on the degree of ventricular dyssynchrony so as to reduce the dyssynchrony and thereby improve cardiac function.

The present invention provides a method of diagnosing the presence or severity of liver fibrosis in an individual by detecting α2-macroglobulin (α2-MG) in a sample from the individual; detecting hyaluronic acid (HA) in a sample from the individual; detecting tissue inhibitor of metalloproteinases-1 (TIMP-1) in a sample from the individual; and diagnosing the presence or severity of liver fibrosis in the individual based on the presence or level of α2-MG, HA and TIMP-1.

A method for conveying both a risk and the degree of risk of a severe weather at a particular geographic location is disclosed. The method involves receiving a location of interest from a requestor, forecasting a risk of severe weather for a specific time period associated with the location, computing a degree of severity level of the risk of severe weather for the location, and generating a report containing the risk forecast and the computed severity level that can be delivered or provided to the requestor. The severity level of the risk of severe weather is provided in an easy to understand graphic or other format.

The invention relates to a safety level evaluation method a power grid, comprising the following steps of: firstly determining a supposed accident list, and sequentially disconnecting elements of the supposed accident list; after a certain element is disconnected, carrying out topological structure analysis and load flow calculation on a system, and then calculating a power grid loss load risk evaluation index, a power grid overload risk evaluation index, a power grid low voltage risk evaluation index and a power grid voltage collapse risk evaluation index; repeating the process till all the elements of the supposed accident list are completely calculated; and then calculating a system single-risk evaluation index and a system total-risk evaluation index. The invention introduces a risk theory and a utility theory to the safety evaluation of the power grid, separately diagnoses the safety of the system from different side surfaces, further obtains the risk evaluation index of the whole system by an analytic hierarchy process (AHP), obtains simple and clear results and has better discrimination and can reflect the occurrence possibility of different accidental accidents and severity degree of a consequence caused by the accidental accidents.

The invention provides online risk analysis system and an online risk analysis method for a regional power grid. The system comprises a display unit, a power grid running risk monitoring unit, an important user monitoring unit, an analysis unit and a risk grading unit; the method comprises the following steps: (1). acquiring the power grid running data and system state; (2). conducting expect fault set selection and fault analysis; (3). judging the result caused by the power grid according to the expect fault, if power supply risk exists, conducting the step (4), otherwise returning the step 2; and (4). calculating risk indicator, and conducting risk grade prompt according to the indicator. The online risk analysis system and the online risk analysis method for the regional power grid comprehensively consider the current state probability, fault possibility and fault seriousness of the system, and help a dispatcher analyze and find hidden risk of the system.

The invention discloses a device for detecting the breakdown of sulfur hexafluoride gas-insulated electrical equipment. The device comprises multiple gas acquisition units. The gas acquisition units are connected with an A/D conversion module (11) wihch is connected with a monitoring and analysis system (12); after SF6 decomposition gas generated from the sulfur hexafluoride gas-insulated electrical equipment is respectively filtered and measured by the gas acquisition units, gas concentration analog signals are obtained, and the gas concentration analog signals are converted to digital signals by the A/D conversion module (11); after the digital signals and the temperature and humidity signals are processed, calculated and analyzed by the monitoring and analysis system (12), a quantitative contrast relationship between the components and concentration of the SF6 decomposition gas and the inner exceptions in the sulfur hexafluoride gas-insulated electrical equipment is obtained to judge the type and the severity of the breakdown and predict development trend of the breakdown; the device for detecting the breakdown is connected with an upper computer by an RS485 or RS232 interface (34) to realize remote communication.

The invention discloses an on-line monitoring device of transformer winding state and a monitoring method thereof. The device is used for the on-line monitoring of transformer winding deformation and bad winding contact and comprises an information acquisition unit, a parameter identification unit, a parameter processing unit and a diagnosis monitoring strategy adjusting unit, wherein the information acquisition unit collects voltage and current information on the original side and the secondary side of the transformer in real time by a data channel; the parameter identification unit identifies the winding resistance and leakage inductance parameter of the winding state of a representation transformer by the real-time voltage and current information provided by the signal acquisition unit; the parameter identification unit calculates the deviation value of a parameter value obtained by analysis and identification and a parameter reference value and takes the deviation value as the characteristic quantity which is used for measuring the quality degree of the transformer winding state; the parameter processing unit and the identification unit ensure the real-time monitoring of the transformer winding state; the diagnosis monitoring strategy adjusting unit judges whether the winding has the defect of deformation or bad contact according to the deviation value of the parameter, and takes corresponding monitoring strategy adjusting scheme according to defect types and severity thereof; and the transformer directly stops operating when the defect is serious.

The invention provides a user identification method and device. According to the user identification method and device, the degree of severity of behaviors of different users can be distinguished, and distinction processing is carried out on the users according to the order of severity of the behaviors. The user identification method comprises the steps of obtaining behavior information of each user, and distinguishing various associated users of each user according to the behavior information, wherein the associated users are users who carry out interaction with the behavior information of the corresponding user; carrying out weighting on the various associated users of each user according to preset risk weights of the associated users according to each user to obtain a risk value of the user; carrying out corresponding monitoring operation and limiting operation on the users according to the risk values of the users.

The present invention provides methods for treating, preventing or reducing the severity of allergic reactions. The present invention also provides methods for enhancing the efficacy and/or safety of an allergen-specific immunotherapy (SIT) regimen. The methods of the present invention comprise administering to a subject in need thereof a therapeutic composition comprising an interleukin-4 receptor (IL-4Rα) antagonist such as an anti-IL-4Rα antibody.

The invention discloses a method for evaluating the degree of a mechanical fault of a frame-type circuit breaker based on a vibration signal. The vibration signal in the method is a mechanical vibration signal collected by a frame-type circuit breaker mechanical fault detection system in the switching process of the frame-type circuit breaker. The method comprises the steps: employing a wavelet packet to carry out the denoising preprocessing of the vibration signal; carrying out the adaptive decomposition of a denoised vibration signal through employing a local mean decomposition algorithm; screening out the former d PF components with the maximum correlation with an original vibration signal; carrying out the improved multiscale arrangement entropy analysis of al PF components, and carrying out the dimension reduction of a feature vector formed by the above improved multiscale arrangement entropy values through the PCA method; building a fault feature vector; constructing a multi-class supporting vector machine, and carrying out the pattern recognition; carrying out the quantitative evaluation of the severity of the mechanical fault happening in the switching process of the circuit breaker through referring to the fault degree characteristic curves in different fault modes. The method is stable, is reliable and is effective.