244 results about "Survival rate" patented technology

The invention discloses a CNN-Transform method based on multi-scale feature interaction, and mainly relates to the technical field of medical image analysis. Comprising the following steps: S1, acquiring sufficient amount of pancreas and tumor CT data, labeling the data, defining an ROI (Region of Interest), and distributing corresponding labels; s2, dividing the data set obtained in the step S1 into a training set and a test set, and preprocessing the training set and the test set by a data enhancement method including random rotation, scaling and mirroring; and S3, a CNN-Transform pancreas and tumor segmentation model PanUNet based on multi-scale feature interaction is constructed. Visual and accurate image information can be provided for doctors through accurate pancreas and tumor segmentation, personalized treatment schemes can be formulated in time, and the survival rate of patients is increased.

The invention relates to a methylation biomarker for detecting colorectal cancer or colorectal adenoma. The methylation biomarker comprises any one gene of SDC2, COL4A2 and C9H9orf50 or any combination of the SDC2, the COL4A2 and the C9H9orf50. Wherein a methylation target detection region of the SDC2 gene is a full-length region of chr8: 96494012-96494130 or a partial region of the full-length region of chr8: 96494012-96494130; a methylation target detection region of the COL4A2 gene is a full-length region of chr13: 110306814-110306983 or a part of the full-length region of the chr13: 110306814-110306983; and the methylation target detection region of the C9H9orf50 gene is the full-length region of chr9: 129620291-129620374 or a part of the full-length region of chr9: 129620291-129620374. According to the kit, methylation signals related to intestinal cancer and adenoma in excrement samples can be more accurately detected through detection in different combination modes of the three markers, the early effective diagnosis rate of colorectal cancer patients can be increased, and therefore the survival rate of the patients is increased, and prognosis is improved.

The invention specifically discloses an intelligent triage classification AR glasses system based on multi-modal data, and relates to the technical field of medical risk management. The system comprises an AR glasses hardware terminal module, a multi-modal data acquisition module, an intelligent analysis processing module, an AR man-machine interaction module, a data storage and transmission module and a peripheral linkage module. Wherein the AR glasses hardware terminal is in lightweight design, the multi-modal data acquisition module acquires and optimizes video, voice, physiology and other data of the wounded, the intelligent analysis processing module outputs red, yellow, green and black triage results through space-time alignment, feature fusion and AI analysis, the AR man-machine interaction module is used for optimizing interaction, and the data storage and transmission module guarantees data safety. And the peripheral linkage module realizes label printing and NFC writing. The system is short in single-time triage time, triage accuracy and environmental adaptability can be improved, information tracing is achieved, two hands of medical care are liberated, and rescue efficiency and the survival rate of wounded personnel are effectively improved.

A method for providing a treatment recommendation to a physician for treating a patient is disclosed. The method comprises determining, from a processor in communication with a patient data repository, a first treatment recommendation based on a combination of selected patient demographics from the patient data repository applicable to the patient, and operational parameters of a plurality of ventricular assist devices (VADs) suitable for treating the patient, the first treatment recommendation having a first survival rate and comprising the use of a first VAD. The method then obtains a first signal from using the first VAD on the patient. The method then determines a second treatment recommendation based on the first signal and the first treatment recommendation, the second treatment recommendation having a second survival rate. The method then provides the second treatment recommendation to the physician if the second survival rate is higher than the first survival rate.

The invention relates to the technical field of biology, in particular to a rice salt stress regulation gene OsMTA1 and application thereof.The rice salt stress regulation gene OsMTA1 is obtained by conducting CRISPR gene editing on the OsMTA1 gene, and compared with receptor rice Zhonghua 11 (ZH11), after two independent strains with mutants knocked out of the transgenic rice OsMTA1 gene are subjected to 180mM NaCl simulated salt stress treatment, the rice salt stress regulation gene OsMTA1 is obtained. After recovery treatment, phenotype observation and survival rate statistics are carried out, it is confirmed that the osmta1 mutant has a salt-sensitive phenotype compared with wild type ZH11, and it is indicated that the OsMTA1 gene plays an important role in the process of responding to rice salt stress.

The invention belongs to the field of tumor medicine and the technical field of molecular biology and gene detection, and relates to application of rs17771861 in preparation of a nasopharyngeal carcinoma prognosis prediction marker, and the sequence of the SNP site rs17771861 is as shown in SEQ ID NO.1. The invention also relates to application of the SNP site rs17771861 in preparation of a nasopharyngeal carcinoma prognosis prediction marker. The invention provides an SNP (Single Nucleotide Polymorphism) marker rs17771861 related to nasopharyngeal carcinoma prognosis, application of the SNP marker rs17771861 and a detection kit capable of being used for nasopharyngeal carcinoma prognosis prediction, and the SNP marker rs17771861 is used for assisting in guiding individualized treatment and improving prognosis of tumor patients. After the kit disclosed by the invention is applied to clinical detection, prognosis of a patient can be evaluated before treatment, and a more positive and effective treatment scheme is formulated for the patient with poor prognosis, so that individualized treatment of the patient is realized, and the survival rate is increased. In addition, the kit only needs to detect peripheral blood, and has the characteristics of convenience in sampling, simplicity in operation, high timeliness and the like.

The invention relates to the technical field of biomedicine, in particular to a liver cancer molecular subtype typing and prognosis model construction method based on glycometabolism and lactic acid metabolism related genes and application thereof. According to the invention, the typing and prognosis model of liver cancer subtypes is constructed for the first time on the basis of a coordinated regulation network of a glycometabolism gene and a lactic acid metabolism gene, the constructed liver cancer subtype subtypes comprise Cluster1 and Cluster2, and the total survival rates of different subtypes have significant difference; the clinical characteristics T.stage and TNM.stage of different subtypes are obviously different from each other; 12 kinds of immune cells have significant differences among different subtypes; iPS immune scores of different subtypes are significantly different; the TIDE scores of different subtypes have significant score differences; the genes with the highest mutation frequency in different subtypes comprise TP53, CTNNB1 and TTN. CLM scores of the prognosis model constructed on the basis of the collaborative regulation network of the glycometabolism genes and the lactic acid metabolism genes have no significant difference in different patient states; the 17 immune cells have significant differences between high and low risk groups. And a new way is provided for individualized treatment strategy formulation and survival outcome improvement of HCC.

The invention discloses a drug screening method based on endotoxin attack, and relates to the technical field of drug screening, in the process of drug screening by using an experimental animal, firstly, an experimental animal model with diseases is established, a certain dose of endotoxin is given to the experimental animal for a period of time after the model is successfully built, and then the experimental animal is subjected to drug screening. And establishing evaluation indexes by utilizing a mathematical formula, and comprehensively evaluating the effectiveness and the safety of the medicine. The evaluation indexes comprise an endotoxin attack survival rate, a survival disease control rate and a survival disease control index. The method can be applied to screening of drugs for treating different diseases, and a more scientific and reliable screening method is provided for research of preclinical drugs or treatment methods.

The invention discloses a lung cancer patient dynamic survival prediction model based on multi-dimensional clinical data, and relates to the technical field of cancer survival prediction, and the key point of the technical scheme is that the dynamic survival prediction model comprises a core model module and a data support module, the core model module comprises a graph convolutional neural network model, a long-short-term memory network model and a generative large language model, and the data support module comprises three data processing systems, namely a time-dependent variable, a time independent variable and a data balancing strategy. According to the dynamic survival prediction model based on combination of traditional Chinese medicine and western medicine, abundant multivariate data in EHR can be fully utilized, individualized and precise diagnosis and treatment of the patient can be realized, artificial intelligence is assisted, and dynamic prediction of the survival rate of the lung cancer patient in one year, two years and three years can be effectively realized.

The invention relates to the technical field of biological and medical diagnosis, in particular to a biomarker for predicting whether a patient suffering from pyotoxic myocardial injury has a short-term death risk or not and application of the biomarker, and the biomarker is the ratio of erythrocyte distribution width to albumin. According to the method, retrospective queue research design is adopted, two data sets, namely MIMIC-IV and eICU-CRD, are used, suppurative myocardial injury patients meeting conditions are included, covariants such as baseline features, laboratory inspection results and complication information of the patients are collected, the patients are divided into two groups according to RAR medians, the relation between RAR and short-term death of the patients is analyzed by adopting multiple statistical methods, and the accuracy of the short-term death of the patients is improved. A risk prediction model of short-term death of the patient suffering from the pyotoxic myocardial injury is constructed, so that a clinician can identify the patient suffering from the pyotoxic myocardial injury with high death risk in an early stage, a personalized treatment strategy can be formulated more accurately, the survival rate of the patient suffering from the pyotoxic myocardial injury is increased, and the method has a wide application prospect.

The invention belongs to the technical field of mandarin fish culture, and relates to a mandarin fish domestication survival rate prediction method and system based on ecological simulation. Establishing a quantitative relation between the ecological factors and the sample mandarin fish survival rate change slope based on the quantitative relation so as to form an evaluation model; a historical survival rate curve is generated, and the risk state is determined by comparing the current sample mandarin fish survival rate change slope with the slope of the historical survival rate curve in the corresponding time section; calculating a change path of the ecological factors in a future time period based on the evaluation model, generating a predicted survival rate curve, and outputting an analysis report containing a risk state judgment result; according to the method, a complex domestication process is converted into a quantifiable data model, and early-stage accurate early warning of the risk is realized through dynamic analysis of the change trend of the survival rate.

The invention discloses a hospital infectious disease recognition and early warning method and system based on big data and artificial intelligence, and relates to the technical field of infectious disease recognition and early warning, and the method comprises a data collection module which is used for collecting multi-source data, and the multi-source data comprises information data of a hospital, environment sensor data and migrant bird migration track data; the data processing module distributes data source weights for multi-source data, and the intelligent early warning module is used for generating a self-adaptive early warning threshold value according to standardized data and historical data and triggering graded early warning according to the generated self-adaptive early warning threshold value; a migrant bird migration track and environmental sensor data are fused, for example, a migrant bird migration abnormal track and environmental virus survival rate parameters are linked, a hospital information system and non-medical data are in butt joint through a standardized interface, and a dynamic time warping algorithm is adopted to calibrate time axis offset of multi-source data, so that the migrant bird migration accuracy is improved. The problem that sensor data and medical record time sequences are inconsistent is solved.

The invention belongs to the technical field of gene engineering, and relates to an esophageal squamous cell carcinoma diagnostic kit based on a peripheral blood mononuclear cell methylation marker and application. The kit comprises a primer pair which is used for detecting the methylation of a cg05914150 site, a cg06769875 site, a cg07475126 site, a cg08433285 site, a cg10038907 site, a cg17968322 site, a cg19572487 site, a cg20184330 site, a cg22741248 site and a cg22823192 site. According to the detection kit provided by the invention, the type of a detected sample is peripheral blood, the sample is relatively easy to obtain and non-invasive, and the patient compliance is relatively good. Abnormal methylation changes mostly exist in the early progression process of tumors, early diagnosis of ESCC can be achieved through the methylation detection method provided by the invention, and the five-year survival rate of ESCC patients is effectively increased.

The invention relates to the technical field of biological medicine, in particular to construction and application of a candida patient death risk prediction model. The model is based on traditional SOFA scoring, core variables are screened through single-factor and multi-factor logistic analysis and LASSO regression analysis, respiratory system, blood coagulation function and circulatory system SOFA scoring and key indexes such as the maximum lactic acid value, the minimum albumin value and the maximum blood urea nitrogen (BUN) are integrated, and a prediction model is constructed through logistic regression. Through multi-center data verification, the AUC of an internal verification queue reaches 0.826, the AUC of an external verification queue is 0.813, and a calibration curve shows that the predicted death rate is highly consistent with the actual death rate. Patients can be divided into a high risk group and a low risk group through a 13-score threshold value, and the 28-day survival rate difference is significant (plt; 0.05) of the method. An efficient and convenient early risk assessment tool is provided for critical candida patients, and clinical precise intervention and prognosis improvement are assisted.

The invention belongs to the technical field of molecular biology, and particularly relates to a construction method and application of a streptococcus pneumoniae pneumonia animal model. The invention provides a construction method of a streptococcus pneumoniae infected rat pneumonia and kidney injury model. The method comprises the following steps: S1, applying a streptococcus pneumoniae liquid into the respiratory tract of a rat by adopting an atomization bacterium feeding mode; and S2, verifying whether the rat treated in the step S1 is infected with pneumonia or not and whether kidney injury exists or not. According to the method, whether pneumonia is infected or not is judged by detecting inflammatory factors in alveolar lavage and lung HE staining, and whether kidney injury exists or not is judged by detecting the urine protein / creatinine ratio in a rat urine sample and detecting kidney HE staining. The construction method provided by the invention is convenient to operate, accurate in model construction and high in survival rate.

The invention discloses a prawn health status assessment method based on multi-source information fusion, and relates to the technical field of data processing. Comprising the following steps: obtaining prawn images in different growth stages and preprocessing the images, generating training images by using artificial marks, and extracting characteristics such as the contour length, the area and the shell contrast of prawns; based on the training image, establishing a target identification and feature extraction model, after training, identifying prawns in the to-be-monitored culture environment and extracting behavior feature parameters of the prawns; calculating a behavior evaluation influence coefficient and a growth evaluation influence coefficient, and obtaining a water source characteristic parameter to calculate a disease incidence influence coefficient; and finally, comprehensively generating a health state evaluation index, comparing the health state evaluation index with a health judgment threshold value, and outputting a health state judgment result, thereby realizing effective evaluation, real-time monitoring and early warning of the prawn health state to help a farmer to take measures in time and prevent diseases, and improving the survival rate and economic benefit of prawn culture.

The invention discloses a generic cancer prognosis biomarker and an application thereof in evaluating the poor prognosis of the generic cancer, which can predict the outcome of a generic cancer type cancer, can be used as a reliable biomarker of a treatment target, and helps clinicians to predict the disease progression and survival rate of patients. The VANGL1 gene is a VANGL1 molecule and comprises a VANGL1 gene and a protein coded by the VANGL1 gene.

The invention discloses an application of NF-kappa B and IRF4 in prognosis evaluation of diffuse large B-cell lymphoma, relates to the technical field of disease prognosis and molecular biology, provides a marker for prognosis evaluation of diffuse large B-cell lymphoma, and relates to the application of NF-kappa B and IRF4 in prognosis evaluation of diffuse large B-cell lymphoma. The invention relates to application of a substance for detecting the marker in claim 1 in preparation of a product for prognosis evaluation of diffuse large B-cell lymphoma, and provides a medicine for treating diffuse large B-cell lymphoma. By detecting the marker, the malignancy degree of the DLBCL can be more accurately analyzed, a reliable prognosis evaluation basis is provided for clinicians, and accurate prognosis evaluation is carried out; through targeting NF-kappa B and MUM1 dual-blocking therapeutic drugs, the prognosis of patients is improved, the life quality and the survival rate of the patients are improved, and novel therapeutic drugs are developed; a new breakthrough is brought to diagnosis, treatment and prognosis evaluation of the DLBCL, and potential clinical application value is achieved.

The invention relates to the technical field of biological medicine, in particular to application of a creatine related gene detection reagent in preparation of breast cancer prognosis products. The creatine related gene is an IGFBP1 gene and / or a TBC1D4 gene. According to the method, the expression levels of IGFBP1 and TBC1D4 genes in breast cancer patient samples are detected, a risk score is calculated by using a random survival forest (RSF) model, and the one-year, two-year and three-year survival rates of breast cancer patients are accurately predicted according to the risk score result. Meanwhile, the invention proves that IGFBP1 and TBC1D4 genes can be used as potential targets for breast cancer treatment, the IGFBP1 and fulvestrant as well as the TBC1D4 and vinblastine have stable binding capacity, and a new basis is provided for selection of individualized treatment medicines for breast cancer.

The application provides a pig breeding and production integrated house group transfer planning and scheduling method and device, and relates to the technical field of intelligent breeding management. Through the fusion of health monitoring and reproductive performance double-dimensional data, the pigs are comprehensively rated and prioritized, so that the group transfer decision is no longer dependent on a single index or artificial experience, and high-value breeding pigs and pigs that need to be isolated can be accurately identified. In the process of combining pigs, the pig pathogen carrying state or health risk level is combined, and the same state priority merging principle is followed, so that the flow of different health state pigs is blocked, and biological safety control is strengthened. According to the loading scheme and the layout of the field, the target field is dynamically allocated and the transfer path is generated, the efficiency of the field is improved, and the stress of the pigs and the lag of the environmental control caused by the transfer confusion are reduced. Through scientific planning of the transfer process, the risk of disease outbreak and treatment cost are reduced, the smooth connection of each breeding link is ensured, and the survival rate of the pig group and the comprehensive breeding benefit are improved.

The invention provides an illness state tracking and early warning system based on a knowledge database, and the system comprises a data module which is responsible for collecting and integrating clinical knowledge and patient data information in the cardiovascular field; the survival rate prediction analysis module is used for extracting pathological features from the patient model, performing survival rate prediction analysis by using a deep learning algorithm and a neural network model, and displaying a prediction result to a physician in a visual report form; and the illness state auxiliary tracking, studying and judging module monitors the illness state change of the patient in real time, analyzes the illness state development trend and risk factors in combination with a knowledge graph and a patient model, and provides treatment scheme recommendation and early warning notification functions. Through the beneficial effects of integrating medical resources, improving data security, accurately predicting the survival rate of a patient, monitoring and early warning in real time, widely applying a knowledge graph, being friendly to user interaction, feedback circulation and continuous optimization and the like, powerful support is provided for prevention, diagnosis and treatment of cardiovascular diseases.

The invention belongs to the technical field of medical detection, and particularly relates to a method for detecting killing activity of immune cells, a product and application. Target cells are subjected to fluorescence labeling through fluorescence labeling (such as carboxyl fluorescein diacetate succinimide ester, CFSE), and then the intensity change of fluorescence signals in a target cell population is quantitatively analyzed by utilizing the high-sensitivity detection characteristic of flow cytometry. Based on the correlation between the fluorescence signal intensity and the cell survival state, establishing a mathematical model to calculate the relative survival rate of the cells. The detection method provided by the invention is simple and convenient in operation flow, and sample preparation can be completed only by single dyeing; and the detection process is rapid, the experiment cost is low, and the kit has wide applicability and important clinical transformation value in the application level.

The invention provides a biomarker for predicting chemosensitivity of acute myelogenous leukemia and application of the biomarker, and belongs to the technical field of biological medicine. The leptin and fumaric acid provided by the invention can be used as biomarkers for predicting AML chemotherapy resistance. Wherein the leptin influences the chemotherapy sensitivity by regulating metabolic pathways such as mitochondrial OXPHOS and mitochondrial active oxygen mtROS; meanwhile, the invention also discloses a new mechanism that fumaric acid promotes BMSCs to transfer mitochondria to AML cells so as to enhance the OXPHOS level and induce Ara-C drug resistance. The levels of the two are obviously related to the chemotherapy reaction and prognosis stratification of the patient, so that early recognition of the patient with chemotherapy resistance or poor prognosis is facilitated. Leptin and fumaric acid can be detected in bone marrow plasma, the feasibility is high, and clinical transformation is facilitated. By detecting the level of leptin or fumaric acid in bone marrow of a patient, individualized treatment can be achieved, and the survival rate of the patient is increased.

The invention relates to the technical field of biological medicine, in particular to application of UL16 binding protein 2 (ULBP2) as a colorectal cancer (CRC) marker. Diagnostic performance of ULBP2 expression is analyzed and evaluated through a subject working characteristic (ROC) curve, the result shows that the ULBP2 is remarkably and highly expressed in CRC tissue, the high expression level is related to remarkably shortening of the overall survival (OS) of a patient, and good diagnosis and prognosis values of the ULBP2 are shown. Functional experiment results show that knock-down of the ULBP2 gene significantly reduces the survival rate and proliferation ability of HCT-8 and LoVo cells, and effectively inhibits tumor cell migration, indicating that the ULBP2 inhibitor has good application prospects in development of colorectal cancer treatment drugs. The invention provides a new biomarker and a treatment target for diagnosis, prognosis and treatment of colorectal cancer.

The invention discloses application of PMF1 as a target spot in preparation of a product for diagnosing, preventing and / or treating hepatocellular carcinoma. According to the invention, the expression conditions of PMF1 in tumor tissues and normal liver tissues in hepatocellular carcinoma specimens are analyzed by using data of an on-line database, and it is found for the first time that the expression of PMF1 in hepatocellular carcinoma is up-regulated and the total survival rate of hepatocellular carcinoma patients with high PMF1 expression is low. Furthermore, experiments prove that the expression of the PMF1 in a hepatocellular carcinoma cell line is obviously higher than that of normal hepatocytes, proliferation, clone formation, migration and invasion of hepatocellular carcinoma cells can be effectively inhibited by reducing the expression level of the PMF1, and it is proved that interference on PMF1 gene expression can become a new way for preventing and / or treating hepatocellular carcinoma.

The invention provides a connecting rod fatigue life evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining connecting rod fatigue life original data under multistage loads, constructing a structured data set, and training a deep neural network model according to the structured data set; predicting the life uncertainty of each load point in a preset target load range according to the trained network model, selecting the load point with the maximum life uncertainty to perform a fatigue test, and updating the network model according to a test result to obtain optimized S-N curve parameters and life distribution parameters; and based on the real-time load spectrum data, the optimized S-N curve parameters and the life distribution parameters, carrying out variable-amplitude load life calculation through a life distribution formula and a damage formula to obtain real-time fatigue life and damage contribution degree distribution under different preset survival rates. The accuracy of fatigue life evaluation of the connecting rod is improved, and accurate prediction and dynamic evaluation of the fatigue life under different survival rates are realized.

The invention provides a medical instrument skin stimulation test data processing method based on an artificial skin model, and relates to the technical field of skin stimulation tests. Collecting the original OD value of each pore in the 96-pore plate under the wavelength of 570nm; calculating the survival rate and the standard deviation of the positive control group and the test sample group; verifying the data validity of the negative control group and the positive control group; and performing skin irritation judgment according to the average survival rate of the test sample group to obtain a skin irritation type. According to the method, the in-vitro skin model based on HTWSkinRHE is established, strict standardized culture conditions and grouping design are adopted, the batch-to-batch consistency and data comparability of the experimental model are remarkably improved, and the model can better meet more medical instrument requirements; the cell activity is detected by simulating a complete skin layered structure and combining an MTT method, and the judgment threshold value is highly matched with the in-vivo stimulation response.

The invention relates to the field of biological medicines, and discloses application of serum EPSTI1 in preparation of a product for diagnosing liver cancer and evaluating whether a liver cancer patient is resistant to a revatinib or not. The invention provides a detection means which is convenient and rapid in sampling, small in risk and relatively low in cost, the content of EPSTI1 in serum is detected through an enzyme-linked immunosorbent assay, a liver cancer patient and a non-liver cancer patient can be effectively distinguished, and a lovatinib drug-resistant liver cancer patient and a non-drug-resistant liver cancer patient can be effectively distinguished. Prognosis analysis shows that the serum EPSTI1 can be used as a marker for evaluating the prognosis state of the liver cancer patient taking the lenvatinib, and has important significance in improving the survival rate of the liver cancer patient.

The invention aims to provide the method for detecting, preventing and treating common diseases of the pomfret in the industrial aquaculture mode, so that the problem that the pomfret is easily infected by parasites, bacteria and viruses in a high-density aquaculture environment to cause large-scale death is solved, and the survival rate of artificially cultured pomfret is increased. According to the method, the disease condition of the bred pomfret can be simply and efficiently detected in a time-saving and labor-saving mode, a large number of experimental equipment is not needed, and operation can be conducted on the first line of pomfret breeding. Disease conditions can be found in the first time, control measures are taken in time, and the breeding survival rate is increased.

The invention discloses an ACS patient prognosis prediction method, which is characterized in that ACS patient prognosis is predicted through a trained and verified ACS patient prognosis prediction model, and prediction factors of the prediction model comprise patient age, heart rate, heart function grading, urea nitrogen and glycosylated hemoglobin. The predictive factors are screened by adopting multi-factor Cox regression analysis. The prediction model comprises a column chart model, and a column chart scale comprises a scale score range of 0-100, a patient age range of 25-95, a heart rate range of 40-140, a heart function grading range of I-IV, a urea nitrogen range of 0-35, a glycosylated hemoglobin range of 4-15, a total score range of 0-240 and a survival rate range of 0.99-0.01.