11results about How to "High screening accuracy" patented technology

The application relates to a work item data processing method, device, equipment, medium and product. In the method, in response to a processing request, work item data corresponding to a plurality of work items is acquired; the work item data comprises assigned user information, closed user information and output submission information; for any work item, the output submission information corresponding to the work item and the output submission information corresponding to a plurality of other work items are compared to determine a duplication result; according to the assigned user information and the closed user information corresponding to the work item and the attendance information corresponding to the assigned user information, a replacement completion result is determined; when the duplication result or the replacement completion result meets a reality condition, the work item is determined as a target work item, and a problem type corresponding to the target work item is determined; according to the task man-hours corresponding to the target work item and the problem type corresponding to the target work item, deduction man-hours corresponding to the assigned user information are determined to perform deduction processing. The screening accuracy of the target work item is improved.

The invention provides a key value caching method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a plurality of text segments corresponding to a current text and a segment attention score corresponding to each text segment; based on the fragment attention score, screening at least one target text fragment from the plurality of text fragments; performing attention analysis on the plurality of candidate lexical elements in the at least one target text fragment to obtain first attention scores corresponding to the plurality of candidate lexical elements; based on the first attention score, screening out at least one target lexical element from the plurality of candidate lexical elements; and updating the original cache based on the key value cache corresponding to the at least one target lexical element. By utilizing the embodiment of the invention, the recall of the key value cache of the target lexical element can be realized, the information loss caused by relatively far lexical element information is avoided, the reasoning of relatively long context can be supported, and the problem of precision loss caused by information loss in a rarefaction process is alleviated.

The embodiment of the present application relates to a kind of method and device for predicting early Alzheimer disease in combination with cognitive characteristics, the method comprises: the deep learning model of early Alzheimer disease three classification prediction based on pathological cognitive multi-modal feature is constructed to obtain the first prediction model;By collecting and analyzing the pathological cognitive multi-modal information of three kinds of crowd to construct the first data set;First prediction model is trained based on the first data set;After training, the pathological cognitive multi-modal information of any individual input by user is received as multi-modal feature input first prediction model and is processed to obtain corresponding prediction vector, and the classification type corresponding to the maximum prediction probability in vector is regarded as the prediction result of current individual and is fed back to current user.The present application can improve screening accuracy, reduce the misdiagnosis rate of cognitive resilience individual.

This invention discloses a cable production identification and monitoring system and method based on cable images, belonging to the field of image recognition technology. The system includes: acquiring a sequence of cable surface depth images to construct a grayscale surface map along the cable surface depth direction; using the central ridge of the grayscale surface map as a dynamic axis of symmetry, detecting candidate pixels through multi-scale morphological top-hat transformation to form a symmetrical residual distribution map; combining the eight-neighbor gradient direction field and Hessian matrix curvature to remove false defect points, obtaining an effective image, and inputting it into a pre-trained multi-task neural network to simultaneously output a defect segmentation mask and category label; generating a three-dimensional mesh model with dimensional accuracy through Poisson surface reconstruction; and finally, using the physical coordinates of the defect center to drive a laser marking machine to mark a QR code containing key information, which is then associated and stored in a blockchain database. This application improves the accuracy and efficiency of defect identification, realizing the quantitative characterization and full lifecycle management of defects.

This invention relates to the field of drug sorting and screening technology, and discloses a drug storage device and intelligent drug sorting method based on AI deep learning. The device includes a drug storage unit, a data acquisition and display unit, a decision management unit, a storage environment control unit, a drug screening unit, and a drug output and recycling unit. The data acquisition and display unit is used for user input of stored drug information, high-definition photography of the drugs, and the use of AI recognition technology to achieve visual recognition and measurement of the drug's appearance and dimensions. Continuous deep learning improves the accuracy of drug appearance recognition, facilitating the drug screening unit's selection of drug quantities. The drug screening unit automatically sorts and selects the required quantity of drugs for patients at specific times, based on different drug dosage regimens. This invention effectively solves the problem of low patient medication adherence, is highly practical, reliable, has low implementation costs, and targets a large beneficiary group.

The invention belongs to the technical field of autism screening, and discloses a rapid interactive screening test method for infant autism, which is suitable for Chinese environment infants of 18-36 months old. The method comprises the following steps: determining an adaptive test object, preparing a test, executing an interactive test and scoring according to a sequence that the first three items are fixed and the other items are flexible, adding scores of the nine items, and judging the risk according to the total score. The method can be completed within 5-10 minutes and is adaptive to Chinese culture, equipment is simple, operation is standardized, and the problems that an existing tool is poor in adaptation and low in efficiency are solved; the method is high in accuracy, is suitable for multiple scenes such as communities, can quickly recognize autism risks, and provides support for early intervention of child autism.

The application discloses a marker for screening aggressive social harmful behavior, a screening method and device and a storage medium, and relates to the technical field of aggressive social behavior screening. The reagent comprises a reagent for detecting relative abundance data of a microbial combination at the genus level. When the 13 kinds of bacteria are used for screening aggressive social harmful behavior, the screening accuracy is extremely high, and the screening method is non-invasive and objective. When the 13 kinds of bacteria are combined with social demographic information as screening factors of aggressive harmful social behavior, the screening accuracy is also extremely high. The application provides a new way for screening and intervention of aggressive social harmful behavior.

A signal weak feature extraction method and system mainly includes the following steps: obtaining original vibration signals of a non-circular gear housing in an electromechanical device under normal and fault states and the like, decomposing the original vibration signals according to an improved empirical wavelet transform, and extracting a frequency band instantaneous envelope line of the decomposed signal components combined with an improved sequential statistical filter; then, combining preset constraint criteria such as a multi-scale correlation criterion, an entropy criterion and a fault feature frequency matching criterion, a weak feature signal modal component in the original vibration signal is screened out. The method can effectively improve the extraction effect of the non-circular gear signal weak feature, reduce the influence of noise and interference signals, improve the screening accuracy of the weak feature signal component, and help improve the accuracy of fault diagnosis and analysis.

The invention discloses a method for improving screening accuracy of specific primers of Shigella by using fluorescent loop-mediated isothermal amplification and a high-resolution melting curve, and belongs to the field of molecular biology. The method comprises the following steps: designing a primer group through an ipaH gene, extracting Shigella genome DNA, taking the Shigella genome DNA as a template, carrying out a fluorescent LAMP amplification reaction on the designed LAMP primer group, and carrying out HRM analysis on an amplification product; the positive amplification curve in the amplification curves is in a typical S shape, the negative control is not amplified, or the peak time of the amplification curve lags the positive peak time by more than 30 min is screened as a specific primer; in an HRM melting curve, a positive template is in a single sharp peak shape, and the positive Tm value is 90.0-91.0 DEG C; the negative control does not have a specific melting peak or has a wide and blunt non-specific peak, and the difference value between the negative control Tm and the positive Tm is greater than or equal to 2.0 DEG C. Through dual verification of fluorescent LAMP and HRM accurate analysis, the advantages and disadvantages of the primers are accurately evaluated, accurate and efficient screening of the optimal primer group is realized, and sensitive and specific primers are provided for subsequent LAMP detection tests.

The application discloses a lung disease pathological whole-section image interest region extraction method and system, relates to the extraction of an interest region, and aims to solve the technical problem of low extraction accuracy of the interest region in the prior art. The method comprises the following steps: acquiring lung image data and calculating the semantic similarity score and the visual feature vector of each block; obtaining an optimal threshold value according to the semantic similarity score and screening out an index set; performing clustering processing on the visual feature vectors of the blocks in the index set, selecting the block with the highest semantic similarity score in each cluster as a representative block, and obtaining the index set; based on the index set, extracting the feature matrix of each representative block, and backtracking the index to the spatial coordinate positions of the representative blocks in the corresponding lung image data to obtain the interest region. The interest region is filtered and identified through adaptive thresholding according to the semantic similarity score, and the selected interest region retains the heterogeneous distribution of different infiltrative features in the section.

The present application relates to artificial intelligence, and provides a drug candidate library construction method, device, equipment and storage medium. The method performs site mutation on the initial protein to obtain a new protein, performs graph characterization on the new protein and the initial protein to obtain a new characterization vector and an initial characterization vector, calculates a spatial structure loss value of the new protein and the initial protein, inputs the new characterization vector and the spatial structure loss value into a protein property prediction model to obtain a predicted property, and screens a target protein from a plurality of new proteins. Amino acid sequences are generated based on antigen-antibody complexes and disease antigens, and the target protein and the amino acid sequences are combined to improve the rationality of generating the drug candidate library. In addition, the present application also relates to blockchain technology, and the drug candidate library can be stored in the blockchain.