18results about How to "High diagnostic value" patented technology

The invention relates to an adaptive weighted bilateral filtering deconvolution OCT image processing method and system, and the method comprises the steps: carrying out the preprocessing of an original OCT signal, including background noise removal, wave number calibration, spectrum shaping and dispersion compensation, so as to obtain an OCT reconstructed image; enhancing the contrast ratio through histogram stretching, adjusting the space weight and the intensity weight of the OCT stretching image, and performing adaptive denoising on the image; and further optimizing the image by using a blind deconvolution algorithm, and iteratively updating the estimated image and a point spread function (PSF) to obtain a high-definition OCT reconstructed image. According to the method, efficient denoising and detail reservation of the OCT image are realized through adaptive weighted bilateral filtering and blind deconvolution technologies, so that a high-definition reconstructed image is obtained.

This invention belongs to the field of biomedicine and relates to the application of a detection reagent for a marker of mixed connective tissue diseases. This invention discloses... MEF2C Genes can serve as biomarkers for mixed connective tissue disease; they are found in the peripheral blood of patients with mixed connective tissue disease. MEF2C Gene expression levels were significantly higher in the group than in the healthy group. This invention provides a detection reagent for a mixed connective tissue disease marker, comprising an upstream primer with the nucleotide sequence shown in SEQ ID NO.3 and a downstream primer with the nucleotide sequence shown in SEQ ID NO.4, which can detect... MEF2C Gene expression levels, which can then be used to develop products for the early diagnosis of mixed connective tissue diseases.

This invention relates to the field of medical image processing, specifically to a multimodal medical image fusion system and method, comprising a data preprocessing module, a domain manifold embedding module, a hierarchical adaptive domain alignment network module, a multimodal feature fusion module, and a diagnostic decision module. The system establishes a topological correspondence between EBUS ultrasound, OCT tomography, and DWI functional images through a multidimensional domain manifold embedding structure; employs a hierarchical adaptive domain alignment network to achieve multi-scale feature extraction and precise alignment; designs a topology-preserving multimodal feature fusion mechanism to ensure the complete preservation of key diagnostic information from each modality during the fusion process; and utilizes a dual-path cross-validation decision strategy to improve the stability and reliability of diagnosis. The system inputs the domain-aligned multimodal features into a Transformer network and generates nodule detection and benign / malignant classification results through dual-threshold judgment, achieving accurate and non-invasive diagnosis of small lesions such as pulmonary nodules and early gastrointestinal lesions.

The invention belongs to the technical field of biology, and discloses a detection method of non-white proteinuria and application of the non-white proteinuria in auxiliary diagnosis of metabolic syndrome. The non-white proteinuria detection method comprises the following steps: S1, carrying out qualitative analysis on a urine sample to obtain qualitative detection results including urine pH, PRO and BLD; if the BLD is positive, judging that the urine sample is suspected non-white proteinuria; if the BLD is negative, executing the step S2; s2, according to the urine qualitative detection result, a urine sample quantitative detection mode is selected to carry out TPU and MALB quantitative detection on the urine sample, and a quantitative detection result is obtained; and jointly judging whether the urine sample is non-white proteinuria or not according to TPU and MALB quantitative detection results and PRO qualitative detection results. The invention also provides a non-white proteinuria detection system which comprises a laboratory information system, an IS system and a urine quantitative analysis system. The non-white proteinuria detection method can realize identification of white proteinuria and non-white proteinuria in proteinuria, and provides a new way for clinical diagnosis of MetS.

The present invention discloses colorectal cancer metabolic markers and their application in diagnosing colorectal cancer. The present invention collects samples from colorectal cancer patients and healthy controls, performs metabolomics analysis, and discovers key metabolic markers related to colorectal cancer and important metabolic pathways related thereto. The present invention discovers for the first time that the above-mentioned metabolic markers show significant differences between colorectal cancer patients and healthy people. Model validation shows that the above-mentioned metabolic markers have high AUC values ​​for diagnosis, and have good predictive effects on early colorectal cancer patients and colorectal precancerous lesions, indicating that the above-mentioned metabolic markers have good clinical use and promotion value.

This invention belongs to the field of engine turbocharger testing technology and discloses a method and system for evaluating the transient response of engine turbochargers. The method includes: test preparation, operating condition setting, transient excitation and data acquisition, calculation of speed increment time, calculation of intake pressure to establish efficiency indicators, and two-dimensional diagnostic evaluation. This invention effectively solves the technical problem that existing evaluation parameters cannot distinguish the root cause of response lag, and has advantages such as accurate positioning and strong guidance. It is particularly suitable for the research and optimization of turbocharger systems with stringent transient response requirements, such as hydrogen fuel cell internal combustion engines.

The invention belongs to the technical field of biological medicine, and particularly relates to application of PPP3CA in renal fibrosis treatment. Researches find that the expression of PPP3CA in fibrotic human renal tubular epithelial cells is up-regulated, and the expression level of PPP3CA in fibrotic kidney tissues of mice is up-regulated; and the renal fibrosis can be obviously relieved by constructing a cell knock-down PPP3CA model and a renal tubule specific PPP3CA knockout mouse to interfere the expression of the renal tubule PPP3CA. Therefore, targeted inhibition of PPP3CA can be applied to prevention, alleviation and treatment of renal fibrosis.

The invention belongs to the technical field of biological medicine, and particularly relates to a biliary atresia differential diagnosis and prognosis marker and application thereof. The invention provides the application of the KRT17 expression level as a biliary atresia differential diagnosis and prognostic marker for the first time. KRT17 as a single marker has a relatively high diagnostic value (AUC = 0.880) for BA, the efficiency of KRT17 is superior to all conventional clinical liver function indexes, and when KRT17 is combined with alanine aminotransferase for use, the diagnostic accuracy can be further improved to AUC = 0.904, the KRT17 and CX3CL1 are optimally combined, and the AUC value is as high as 0.938. According to the technology, KRT17 is used as a novel biliary atresia differential diagnosis marker, the defects of an existing differential diagnosis system can be made up to a certain degree, the KRT17 is specifically and highly expressed in biliary atresia liver bile duct epithelial cells, normal control and disease control are not expressed, and therefore more accurate differential diagnosis can be provided clinically.

The invention discloses a metabolite composition for evaluating children refractory epilepsy and application thereof, and finds that metabolic markers 3-hydroxyvalproic acid, trans-2-octenoic acid, glutamic acid, C-6 ceramide and / or arginine can be applied to diagnosis and / or early prediction of children refractory epilepsy for the first time. Furthermore, it is found that the metabolic marker has an extremely high diagnostic value for children refractory epilepsy, and can diagnose and / or early predict whether a to-be-detected subject suffers from children refractory epilepsy or the risk of suffering from children refractory epilepsy in a high-accuracy, high-sensitivity and high-specificity manner, so that accurate diagnosis and treatment of children refractory epilepsy are effectively promoted; the clinical application prospect is wide.

The invention discloses a multi-modal image fusion method and device based on a graph neural network and a storage medium in the technical field of medical image processing and artificial intelligence. The method comprises the following steps: acquiring a multi-modal image; performing depth feature extraction on the multi-modal image to obtain a high-dimensional feature map of each modal; dividing the high-dimensional feature graph of each modal into a plurality of graph nodes, calculating the similarity between each graph node and an adjacent node thereof, and constructing an adjacent matrix of a multi-modal graph structure according to the similarity; taking an adjacent matrix as graph topology guidance, capturing a global association relationship and a long-distance dependency relationship of node features in graph nodes, and performing global aggregation according to an attention pooling graph reading function to generate global features; and inputting the global features into the reconstruction network to generate a final fusion image. The technical problems that in the prior art, the modeling capacity for irregular data is limited, and complex spatial association and semantic dependence between multi-modal images are difficult to effectively capture can be solved.

The present invention belongs to the field of biomedical technology, and particularly relates to a kit for early diagnosis of lung cancer and its application. The kit includes an enzyme-labeled plate coated with a capture antibody, a working solution of an HRP-labeled antibody, an antigen standard, a washing solution, a chromogenic solution, and a termination solution; the heavy-chain amino acid sequence of the monoclonal antibody F6C-1 against the MAPRE2 protein in the capture antibody is as shown in SEQ ID NO.1, and the light-chain amino acid sequence is as shown in SEQ ID NO.2; the heavy-chain amino acid sequence of the monoclonal antibody H3A-2 against the MAPRE2 protein in the HRP-labeled antibody is as shown in SEQ ID NO.3, and the light-chain amino acid sequence is as shown in SEQ ID NO.4. The kit for early diagnosis of lung cancer provided by the present invention has strong specificity, can be used as an auxiliary diagnostic method for lung cancer with high expression of the MAPRE2 protein, and has high diagnostic value.

The present application relates to the field of data processing, and more particularly to a diagnosis information processing method and system based on big data analysis. The method comprises the following steps: first, obtaining a low-dimensional embedding vector containing symptom diagnosis associated information; then, constructing a structured covariance matrix by solving an optimization problem, wherein the optimization problem takes the sample covariance matrix as a data fidelity term and takes a graph Laplacian matrix derived from the embedding vector as a regularization term, thereby injecting medical knowledge into the matrix structure; finally, using principal components derived from the structured covariance matrix to reduce the dimensionality of high-dimensional diagnosis features. The present application can effectively retain the symptom combination information which is crucial for clinical diagnosis, avoid the loss of key features, and significantly improve the quality of the features after dimensionality reduction.

The invention relates to the technical field of biological medicine, in particular to a marker for FSGS diagnosis and treatment and application of the marker, and aims at solving the problem that in the prior art, a target biomarker for FSGS abnormal expression is not screened out, related data of FSGS is obtained, and analysis and machine learning screening are conducted on the data, so that the target biomarker for FSGS abnormal expression is obtained. Five key target genes, namely JUN, PLK2, AKR1C3, PTGS2 and HSD11B2, related to the FSGS are obtained, the obtained key target genes are identified and verified, and it is proved that the five key target genes have high indication efficiency on the FSGS and are ideal drug targets; target spot prediction and enrichment analysis are carried out on the active ingredients of the traditional Chinese medicine, the active ingredients of the medicine are combined with key target genes through a molecular docking technology, the binding affinity of the active ingredients of the traditional Chinese medicine such as semen cuscutae and the like and target protein is verified, and the application prospect of the traditional Chinese medicine composition in the aspect of treating FSGS is further verified; the diagnosis and treatment efficiency of the FSGS is powerfully promoted.

The invention relates to adipose tissue lipid metabolites for evaluating the health state of fat and a detection kit and application of the adipose tissue lipid metabolites. Specifically, the lipid metabolites arachidonic acid and docosapentaenoic acid can be used as markers for evaluating the health state of adipose tissue metabolism; the arachidonic acid can be used for improving obesity metabolic disorder; according to the kit, fat tissue lipid metabolites are rapidly detected, so that the fat tissue is directly and rapidly evaluated; according to the detection kit, the technical requirements on operators are reduced, the operation steps are simplified, and the detection kit can be applied on a large scale, so that early detection and prevention and treatment of obesity-related diseases are improved.

The invention discloses an idiopathic atmospheric hydrocephalus biomarker, a diagnostic kit and application, belongs to the technical field of biological medicine, and particularly relates to the idiopathic atmospheric hydrocephalus biomarker which is a protein biomarker and comprises NBL1, TREM2, COL3A1, DPP7, PLA1A, SELENBP1, FGB, CCK, WFIKKN2, KNG1, HBA2, GFRA3 and CSF1. The invention relates to an application of an idiopathic atmospheric hydrocephalus biomarker in preparation of an idiopathic atmospheric hydrocephalus diagnostic kit. Differential proteins are screened through a DIA technology, protein expression is verified through a PRM technology, the idiopathic atmospheric hydrocephalus biomarker is obtained through screening and used for early screening, risk assessment and prognosis judgment of iNPH, early, accurate and objective diagnosis of iNPH is achieved, the clinical diagnosis period is shortened, and the diagnosis and treatment efficiency is improved.

The invention relates to the technical field of magnetic resonance imaging, in particular to a non-linear mapping parallel imaging reconstruction method and device based on manifold. The method comprises the following steps: acquiring K space data through multiple channels; setting a neighborhood size according to the collected K space data, and adaptively optimizing and adjusting key parameters of high-dimensional mapping; non-linearly related image information and noise components of the K space data are used as feature input and mapped to a higher-dimensional feature space through a popularity method, and a topological relation of the high-dimensional feature space is established; in a high-dimensional feature space, differences between neighborhood points are smoothed through manifold regression, a nonlinear model is established to perform fitting on signal and noise features to complement a down-sampled K space part, and reversible Fourier transform is performed based on reconstructed K space data to recover to an image space. According to the method, the precision and anti-noise performance of the reconstructed image are improved, the application range of the algorithm is expanded, and the problem of low signal-to-noise ratio in low-field-intensity magnetic resonance parallel imaging is solved.

The invention belongs to the technical field of medical biomolecules, and particularly discloses a column diagram construction method for osteoporosis accompanied with atherosclerosis, which specifically comprises the following steps: acquiring a GSE1428 data set, a GSE230665 data set and a GSE1000927 data set from a GEO database; screening out differential expression genes between the osteoporosis and normal tissues and between the atherosclerosis and healthy tissues by using a Limma bag; then performing WGCNA analysis on DEGs, and finally screening differential expression genes by using an LASSO regression algorithm, a random forest and an SVM-RFE algorithm to obtain a potential key common biomarker; based on the key common biomarkers, a column diagram is constructed, an ROC curve is drawn, and the diagnostic ability of candidate common biomarker genes is evaluated to reach 0.99. Based on the column diagram, a prediction system is provided, and a visual basis is provided for clinical diagnosis of osteoporosis with atherosclerosis.

The present invention relates to the field of biomarker technology, and in particular to a biomarker for diagnosing central precocious puberty in women and its application. The present invention provides a biomarker for diagnosing central precocious puberty in women, wherein the marker is one, two or three of Leptin, RBP4 or Chemerin. The present invention has experimentally found that the peripheral blood Leptin, RBP4 and Chemerin levels of female children with CPP are significantly higher than those of healthy children, and the serum Leptin and RBP4 levels change in the early stages of CPP children, suggesting that these three fat factors may be involved in the onset of CPP.