7 results about "Diagnosis Type" patented technology

The invention provides a pneumonia CT image diagnosis model training method, diagnosis method and equipment, and the training method comprises the steps: inputting a 3D chest CT image into a multi-task deep learning model, enabling a shared encoder in the model to extract multi-scale feature data, and enabling a connection module and a decoder to obtain pneumonia focus region prediction result data according to the multi-scale feature data, the classification head obtains pneumonia diagnosis type prediction result data according to the multi-scale feature data; determining the joint loss of the model in the current iteration round and updating model parameters; and if the current multi-task deep learning model satisfies a training termination condition, outputting the current model as a pneumonia CT image diagnosis model. According to the method, the problems of low model feature utilization rate and low pneumonia diagnosis process efficiency caused by incapability of simultaneously completing focus segmentation and type classification due to task simplification of an existing pneumonia diagnosis model can be solved.

The invention discloses a fault intelligent diagnosis type thermal power plant electric power operation and maintenance method and system, and particularly relates to the technical field of thermal power plant electric power operation and maintenance and intelligent diagnosis, the system adopts an edge-cloud-site three-layer collaborative architecture, and comprises a sensing module, an edge processing module, a cloud core module, a site execution module and an optimization iteration module; the method is based on the system, combines technologies of federated learning, digital twinning and the like, and forms a closed-loop mechanism through full-dimension data acquisition and preprocessing, three-stage twinning model construction and updating, three-mode fusion fault diagnosis, differentiated operation and maintenance treatment and model self-optimization. The problems that traditional operation and maintenance cross-equipment fault tracing is difficult, and data safety and sharing are contradictory are solved, the diagnosis accuracy is larger than or equal to 98.5%, early warning level faults are pre-judged 3-6 hours in advance, the operation and maintenance cost is reduced by 30% or above, operation and maintenance are promoted to be transformed to active pre-judgment and intelligent optimization, stable operation of a unit is guaranteed, and practicability is remarkable.

The embodiment of the application discloses a data diagnosis method and device, a diagnosis equipment and a storage medium. The method comprises the following steps: receiving a diagnosis request of a target diagnosis type of a target service sent by a diagnosis platform; the diagnosis request comprises a target domain name required to be called when executing the target service and network attribute information of a network used for executing the target service; intermediate data generated when the target service is executed based on the target domain name and the network attribute information is acquired; the intermediate data comprises address data required in the process of executing the target service; diagnosis reference data of the target diagnosis type of the target service is acquired; the intermediate data is diagnosed based on the diagnosis reference data, and a diagnosis result for the target service is obtained; the diagnosis result is used for indicating that a target address indicated by the target domain name can be accessed or cannot be accessed when the target service is executed based on the network attribute information. By using the application, the diagnosis efficiency and diagnosis accuracy for the target service can be improved.

This invention discloses a treatment pathway recommendation method based on IBS multidimensional data. This invention relates to the field of intelligent diagnosis and treatment technology, and includes the following steps: S1, constructing an IBS treatment plan library. The treatment plan library contains standardized treatment plans corresponding to different diagnostic types and severity levels of IBS. The standardized treatment plan includes at least follow-up recommendations, medication recommendations, probiotic recommendations, and nursing guidance, and each treatment plan is associated with a corresponding IBS multidimensional data feature threshold. This treatment pathway recommendation method based on IBS multidimensional data overcomes the limitations of existing technologies with single-dimensional diagnostic data. It comprehensively integrates four core dimensions: patient symptom data, physical sign data, laboratory test data, and medical history data. Symptom data is obtained through a combination of patient self-reporting and doctor consultation to ensure no omissions; physical sign data relies on professional medical equipment to ensure objectivity; and laboratory test data is obtained synchronously from the hospital's testing system to reduce errors.

The invention relates to the technical field of automobile electronic diagnosis, in particular to an automobile online diagnosis method and device, diagnosis equipment and a storage medium, and the method comprises the steps: receiving an encrypted script file which is downloaded from a server and is matched with a diagnosis type according to the diagnosis type selected by a user; decrypting the encrypted script file by using a private key to obtain an executable diagnosis script; and calling an interpreter to run the executable diagnosis script, and calling a dynamic link library function in the diagnosis function dependency library through an interface to complete diagnosis operation on the target vehicle. According to the application, the security of the program is improved, and the risk that the program is cracked is reduced.

This invention proposes a method and system for fault diagnosis of permanent magnet synchronous motor (PMSM) sensors. The method includes: acquiring historical measurement data of the PMSM and constructing a dataset for training a classification model; training the classification model offline using the dataset; inputting the PMSM data collected in the current time window into the trained classification model and determining the reliability of the model's output; if reliable, stopping the diagnosis process in the current time window and outputting the diagnosis type and fault location; if unreliable, proceeding to the next window for diagnosis. Based on this method, a fault diagnosis system for PMSM sensors is also proposed. This invention features high scalability, strong self-learning capability, independence from the motor's physical model, and strong robustness to system noise and external disturbances, appropriately improving the diagnosis speed while ensuring accuracy.

The invention provides a transverse evaluation method and system for diagnosis and treatment capabilities of multiple hospitals, belongs to the technical field of medical big data analysis and hospital performance evaluation, and solves the problem of score distortion caused by data heterogeneity, weight immobilization and the like in the prior art. The method comprises the following steps: preprocessing detection data of a plurality of hospitals on various diagnosis types to obtain a standard diagnosis rate of each hospital on each diagnosis type; calculating the relative proportion of each hospital in the corresponding diagnosis type according to the standard diagnosis rates of all hospitals in the same diagnosis type; according to the relative proportion of all hospitals in the same diagnosis type, determining the comprehensive weight of the corresponding diagnosis type by using an entropy weight method; according to the detection data and the standard diagnosis rate of each hospital on each diagnosis type and the comprehensive weight of each diagnosis type, calculating a comprehensive diagnosis and treatment ability score of the corresponding hospital; and according to the comprehensive diagnosis and treatment capability scores of all hospitals, carrying out transverse evaluation on the diagnosis and treatment capabilities of the hospitals.