11results about How to "Guaranteed difference" patented technology

The invention relates to the technical field of image processing, in particular to a spinal arthritis medical image feature auxiliary identification method, which comprises the following steps: acquiring a T1 weighted image and a T2 weighted image of a spinal MRI image of a patient, and recording the T2 weighted image as an original image; obtaining a target area in the original image; obtaining a mapping adjustment coefficient of each target area according to the edge shape difference and the gray scale difference of each target area and the corresponding area of each target area in the T1 weighted image; acquiring a local enhanced image according to the mapping adjustment coefficient; obtaining a correction enhancement coefficient of each target area; and performing gray stretching on the local enhanced image according to the correction enhancement coefficient of each target area to obtain a final enhanced image. The invention aims to improve the contrast ratio of the area capable of reflecting the spinal arthritis, ensure the difference between the T1 weighted image and the T2 weighted image, and reduce the reading difficulty of the MRI image when a doctor recognizes the spinal arthritis.

The invention provides a joint decision-making method and device based on man-machine mixing, and is applied to the technical field of artificial intelligence. The method comprises the following steps: acquiring visible track information and agent observable state information of an unseen teammate; determining a historical information representation vector according to the visible track information, and determining observable state representation according to the agent observable state information; determining non-teammate style information according to the historical information representation vector and the observable state representation; inputting the non-teammate-seeing style information into a joint decision network based on man-machine mixing to obtain teammate actions; inputting the teammate action into a pulse neural network to obtain a decision action; wherein the joint decision network based on man-machine mixing is constrained through a determinant point process so as to simulate self-learning integration of different styles. Through man-machine cooperation, the ability of teammates can be quickly received, so that a more robust and generalized decision result is obtained.

The invention relates to the field of data processing, in particular to an image generation data processing system based on AIGC, which comprises a data acquisition unit; the state analysis unit is used for determining a conflict coefficient according to the judgment condition and determining a text state according to the quantity of similar keywords and the conflict coefficient; the elimination analysis unit is used for determining a keyword elimination mode of each redundancy combination according to a set condition; the processing judgment unit is used for determining an input state of the standard input text according to the text integrating degree and the feature dimension and determining an image processing mode according to the input state; the first processing unit is used for determining that an image updating mode is all feature updating or determining a key feature updating mode according to a text type and a type of text state according to a judgment condition; the second processing unit is used for directly generating an image according to the keyword; the image generation efficiency can be improved, and the conformity degree of the generated image and the user expectation can be improved.

The present invention proposes a multi-factor special fund reporting overdue prediction method, system, medium and equipment, which belongs to the technical field of fund reporting progress supervision. The method obtains historical project information and a complete reporting path containing node information, extracts time-series evaluation factors including node status, reporting deadline, and fund amount, inputs the trained LSTM model element fusion features, and uses the element fusion features to train and optimize the overdue prediction model to minimize the loss. Subsequently, the current project information is obtained, the element fusion features are extracted and input into the model, the current project reporting path and nodes are predicted, the reporting time is calculated according to the node position, and compared with the warning threshold to realize overdue judgment and warning. The present invention overcomes the problems of difficulty in real-time monitoring, management and supervision of special fund reporting, and low prediction accuracy, and effectively improves the efficiency and accuracy of special fund reporting management.

The application discloses a method and device for constructing a gradient boosting decision tree (GBDT) model, and relates to the technical field of machine learning, and mainly aims to solve the problem of low accuracy of the existing trained decision tree model. The main technical scheme of the application is as follows: obtaining a sample data set, wherein the sample data set comprises positive sample data with positive labels and unlabeled sample data without labels; when training each regression tree of the GBDT model, a positive sample training subset is constructed based on the positive sample data in the sample data set, a negative sample training subset is constructed by sampling the unlabeled sample data in the sample data set, the positive sample training subset and the multiple negative sample training subsets are combined to obtain a training set of the current regression tree, the current regression tree is trained based on the training set of the current regression tree, and a GBDT model is constructed according to each regression tree. The application is used in the construction process of the GBDT.

The invention provides a multi-factor special fund filling overdue prediction method and system, a medium and equipment, and belongs to the technical field of fund filling progress supervision. According to the method, historical project information and a complete filling path containing node information are obtained, a time sequence evaluation factor containing a node state, a filling period and a fund amount is extracted, a trained LSTM model element fusion feature is input, and the element fusion feature is utilized to train and optimize an overdue prediction model until the loss is minimum. And then, obtaining current project information, extracting an element fusion feature input model, predicting a current project filling path and nodes, calculating filling time according to node positions, and comparing the filling time with an early warning threshold value to realize overdue judgment and early warning. According to the invention, the problems of difficulty in real-time monitoring, management and supervision of special fund filling and reporting and low prediction accuracy are solved, and the efficiency and accuracy of special fund filling and reporting management are effectively improved.

The present invention belongs to the technical field of CNV detection, and discloses a CNV detection method, system and reliability verification method based on a small panel. The detection method comprises: obtaining an original data matrix, wherein one column in the original data matrix is ​​the depth data of the sample to be tested, and the remaining columns are the depth data of the control sample; calculating the ratio between each depth data in each row of the original data matrix and the geometric mean of the row to obtain an intermediate data matrix; calculating the ratio between each depth data in each column of the intermediate data matrix and the median of the column to obtain a correction data matrix; solving the ratio between the sample to be tested and the control sample in each amplification region based on the correction data matrix to obtain the CNV type of the sample to be tested. Thereby effectively improving the accuracy of the detection result. The reliability verification method is based on mathematical logic, which is simpler and more feasible than the existing method based on a large number of simulation calculations, and the reliability of the result is better.

The invention provides a page template processing method and device, electronic equipment and a storage medium. The method can be applied to vehicle-mounted scenes and map scenes; the method comprises the following steps: displaying a human-computer interaction interface; in response to a component selection operation in the human-computer interaction interface, obtaining a plurality of page components; in response to a template selection operation in the human-computer interaction interface, at least one page template is obtained, and the page template comprises a plurality of component positions; a trigger operation is generated in response to a template in the human-computer interaction interface, the server is triggered to cluster the multiple page components into multiple combinations, each combination comprises different types of page components, each type in the combinations corresponds to one page component, and the page components in each combination are stored in the server. And inserting a component position having a matching relationship with the page component in the page template to obtain a derived template corresponding to each combination. According to the method and the device, diversified page templates are efficiently generated.

The present invention relates to the field of image processing technology, and specifically to a method for assisting the identification of medical imaging features of spondyloarthritis, comprising: obtaining a T1-weighted image and a T2-weighted image of a patient's spinal MRI image, recording the T2-weighted image as an original image; obtaining a target area in the original image; obtaining a mapping adjustment coefficient for each target area according to the edge shape difference and grayscale difference between each target area and the corresponding area of ​​each target area in the T1-weighted image; obtaining a local enhanced image according to the mapping adjustment coefficient; obtaining a corrected enhancement coefficient for each target area; grayscale stretching the local enhanced image according to the corrected enhancement coefficient of each target area to obtain a final enhanced image. The present invention aims to improve the contrast of areas that can reflect spondyloarthritis, ensure the difference between T1-weighted images and T2-weighted images, and reduce the difficulty of doctors reading MRI images when identifying spondyloarthritis.

The invention discloses a light and convenient-to-operate patient turning-over assisting device which comprises a folding and supporting mechanism, a rubber and plastic block, an end groove, an end convex block, a stop part, a limiting convex edge, a reinforcing pin rod, a silica gel cushion, a hook, a short connecting pipe, an air cylinder, a supporting plate, a J-shaped plate, a positioning bolt and an electric control box. The rubber and plastic block has the beneficial effects that the stop parts arranged at the joints of the rubber and plastic blocks are mounted in the X / Y direction at the equal decreasing height positions, and the limiting stop structures between the limiting convex edges and the corresponding stop parts are combined, so that the difference of the lateral rotation degree of each rubber and plastic block is ensured, the effect of forming a larger turning and supporting slope surface is achieved, and the service life of the rubber and plastic blocks is prolonged. By combining the air cylinder support and the limiting stop structures between the limiting convex edges and the corresponding stop parts, the shape change of the use state of the folding and supporting mechanism is effectively limited, the problem that different shape positioning cannot be kept due to the fact that an auxiliary turning-over structure is soft and easy to loosen is solved, the work intensity of turning over of a patient is greatly relieved, the overall weight is light, and disassembly and assembly are convenient and fast.