59 results about "Meta-analysis" patented technology

The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure. According to various embodiments, methods, systems and interfaces for associating experimental data, features and groups of data related by structure and / or function with chemical, medical and / or biological terms in an ontology or taxonomy are provided. According to various embodiments, methods, systems and interfaces for filtering data by data source information are provided, allowing dynamic navigation through large amounts of data to find the most relevant results for a particular query.

The present invention relates to a method and apparatus to objectively measure stress and fatigue using measurement tools, record stress and fatigue related data in a standardized database, create automated prompts and alerts based upon pre-defined stress and fatigue thresholds (which are derived based upon individual end-user and task performance), provide a number of interventions (which can be preferentially selected by the individual end-user), create data-driven best practice guidelines though meta-analysis of the database, and provide an objective tool for comparative technology assessment.

A system, including methods and apparatus, for performing a digital assay on a number of sample-containing replicates, each containing a plurality of sample-containing droplets, and measuring the concentration of target in the sample. Statistical meta-analysis techniques may be applied to reduce the effective variance of the measured target concentration.

The present invention relates to creating an all-inclusive methodology for data collection and analysis which can serve as a vehicle for pharmaceutical meta-analysis and creation of data-driven best practice guidelines, which represents the cornerstone of evidence based medicine. The present invention includes a number of unique components which record standardized_data throughout a multi-step and multi-stakeholder process, with the end result of creating a standardized method for creating, collecting, storing, communicating, and analyzing data related to the multi-step process of pharmaceutical administration in healthcare. In the course of doing so, a number of unique profiles are created which account for patient and provider differences, which are important in identifying compliance risk factors, causation, intervention, and treatment strategies.

The invention provides a network access control method and system. The method comprises the following steps: monitoring an access request of a user through a filter; obtaining a plurality of access parameters of the user from the access request; carrying out meta-analysis on the plurality of access parameters to obtain an analytical result; and carrying out interception according to the analytical result. According to the method, by means of the meta-analysis of the plurality of access parameters, malicious attacks can be effectively intercepted, and resource depletion is reduced.

The invention discloses a method for extracting a brain function network of an individual based on the analysis of multiple tested brain function data. The method comprises the following steps of: calculating the tested independent components of the individual, having correspondence among the different tested, based on the tested brain function data of the individual; using a provided algorithm for analyzing the independent components with reference signals based on a multi-target function optimization framework, meanwhile, optimizing the correspondence between the tested independent components of the individual and the reference signals and the independence among the different tested components of the individual, wherein the reference signals are obtained by jointly analyzing the independent components of the tested brain function data of the individual, and can also be obtained from a brain network pattern and the like obtained through the brain network analysis or meta analysis of other modal imaging data; after the tested independent components of the individual are obtained, using a provided time sequence calculation method to calculate a time sequence corresponding to each independent component; and judging the obtained independent components to obtain a brain function network, wherein the time sequence corresponding to the independent component is an activating mode corresponding to the brain function network.

The embodiment of the invention provides a field disease and insect pest monitoring system and method. The field disease and insect pest monitoring system comprises an image acquisition processing terminal, a controller, a stepping motor and a server. The image acquisition processing terminal is used for transmitting a motion control instruction to the controller; the controller transmits a motioncontrol signal to the stepping motor according to the motion control instruction; the stepping motor moves on a track according to a control signal; the image acquisition processing terminal photographs disease and insect pest images at multiple sampling points in the motion process of the stepping motor, and analyzes the disease and insect pest images so as to obtain the types and quantities ofthe diseases and insect pests in the disease and insect pest images, and the data records are uploaded to the server in real time; and the server is used for performing meta-analysis on the disease and insect pest records transmitted by the image acquisition processing terminal and realizing early warning of the occurrence trend of the diseases and insect pests. Therefore, the workload and labor intensity of monitoring personnel can be greatly reduced, the monitoring accuracy is obviously increased, and occurrence rules of the diseases and insect pests can be scientifically analyzed and researched.

The invention discloses an FCM-based waterlogging modeling and analysis method, which constructs an FCM model of waterlogging through modeling, and analyzes the occurrence of waterlogging based on the urban rainfall variation trend and waterlogging depth of waterlogging-prone points obtained therefrom. The method proposed by the present invention combines the strong fuzzy information expression and reasoning ability of the fuzzy cognitive map, and the gene-level operation of the DNA-encoded genetic algorithm technology to construct the waterlogging FCM model; the constructed waterlogging FCM model carries out the historical waterlogging data Integrate analysis and utilization, so that the ability of analysis is enhanced. Theoretically, the construction of this model is not restricted by the geographical location of waterlogging occurrence, and only needs to combine the parameter changes of a single waterlogging point under actual conditions to obtain the dynamic change trend of each parameter; therefore, it has great reference value.

The invention discloses an application of a CPE (carboxypeptidase E) gene to preparing a kit for diagnosing osteosarcoma. 8 sets of satisfactory osteosarcoma cases and normal crowd genome mRNA (messenger RNA) expression chip data are taken into a research scope by utilizing NCBI (national center of biotechnology information) GEO (gene expression omnibus) data retrieval; by carrying out Meta analysis onto the chip data, the CPE gene is screened as a difference significant gene; compared with a normal structure, expression of the CPE gene in the osteosarcoma tissue is regulated up, and the conclusion is verified by using a fluorescent real-time quantification PCR (polymerase chain reaction) method. The invention further discloses a kit for diagnosing osteosarcoma and a method for diagnosing osteosarcoma by utilizing the kit. According to the application disclosed by the invention, on one hand, a novel thought is provided for researching a molecular mechanism of the osteosarcoma, and on the other hand, a more flexible diagnostic kit is provided for diagnosing osteosarcoma at an early stage.

The invention provides a data transmission apparatus and method of a client and a data transmission apparatus and method of a server, and relates to the field of Internet communication. The data transmission apparatus of the client comprises a splitting unit used for splitting an HTTP request to form a plurality of data sub-packets; a protocol unit used for sending the plurality of data sub-packets to the server through a UDP; an analysis unit used for obtaining and performing meta-analysis on reception acknowledgement messages corresponding to the data sub-packets and transmitted by the server to find data sub-packets having no reception acknowledgement in the plurality of data sub-packets; a retransmission unit used for retransmitting the data sub-packets having no reception acknowledgement to the server until determining the fact that the server receives all data sub-packets; and a first receiving unit used for receiving HTTP response data transmitted by the server. By adoption of the technical scheme provided by the invention, the problem of too slow webpage request resulting from the instability of a network and the power saving of a mobile phone in a mobile network can be effectively solved.

The invention discloses a method and a device for extracting meta biomarkers. The method comprises the steps that n disease mass spectrometric data sets relevant to the same disease are fetched; protein quantification is conducted on proteins in each disease mass spectrometric data set; n protein quantification results are obtained, wherein n is a positive integer; each protein quantification result is compared with a corresponding reference control group; statistical discrepancy probability values of the proteins in each protein quantification result are obtained; the proteins with the statistical discrepancy probability values less than preset remarkable thresholds serve as candidate biomarkers; m candidate biomarkers are obtained; meta-analysis is conducted on the m candidate biomarkers; and sets of the candidate biomarkers with statistical magnitude greater than preset statistical values in the n disease mass spectrometric data sets are extracted to serve as the meta biomarkers. The method and the device can conduct analysis by utilizing the mass spectrometric data sets which are relevant to the diseases, from separate sources and outputted by different laboratories, and the obtained meta biomarkers have better generality and robustness.

The invention specifically discloses a pesticide residue detection system capable of uploading data in real time, including a pesticide residue detector, a client and a cloud server, and the pesticide residue detector communicates with the client through a Bluetooth communication module or an infrared transmission module , the client is connected to the cloud server through a wireless network, and the wireless network includes WIFI and mobile network. The present invention combines offline detection with cloud technology, relies on intelligent communication equipment and developed mobile network, and conducts a large number of analysis and calculation processes in the cloud, which is beneficial to relevant departments to integrate and analyze sampling detection results and track long-term detection results . The cloud storage of the test results makes the test results traceable.

A modeled-based reasoning system and method including dynamic domain abstraction, includes the use of an abstraction determining module configured to identify an appropriate abstraction level for a system model of a real-world system to be analyzed, from a plurality of potential abstraction levels. A system reasoning module is configured to perform analysis on the system model of the real-world system at the abstraction level determined to be appropriate by the abstraction determining module.

The invention provides a climate change risk analysis and evaluation method, which comprises the steps of determining climate variables and social and economic variables based on historical climate data, historical social and economic data and quantifiable climate policy indexes; respectively constructing a regional economic loss model, a meta-analysis loss model, an extreme disaster loss model and a department climatic loss model from top to bottom according to the climatic variable and the social economic variable; and determining comprehensive climatic change economic loss according to theregional economic loss model, the meta-analysis loss model, the extreme disaster loss model and the department climatic loss model. An economic model and a physical model are coupled, modeling is carried out based on historical data, social and economic risks caused by climate change are evaluated based on future climate change data, the influence of climate change on a social and economic systemis quantified, and probabilistic loss and income caused by climate change are obtained.

The invention discloses a method for screening a kidney cancer peripheral blood miRNA marker and a miRNA marker. The screening method comprises the steps that miRNAs data related to the kidney cancer is summarized, meta analysis is performed, and one or more miRNAs with the best comprehensive analysis result are screened out to be adopted as candidate miRNAs; then, a TaqMan probe-based qRT-PCR method is adopted for perfomring crowd serum / plasma sample verification on the candidate miRNAs, and miRNAs with the expression threshold value of a patient suffering from the kidney cancer relative to healthy human serum / plasma being larger than 2.53 or smaller than 3.12; finally, the expression consistency of the miRNAs in kidney cancer tissue and serum / plasma is verified, and if it is verified that expression consistency is verified, the target marker is obtained. The invention further provides a kidney cancer serum / plasma miRNA marker miR-378. A novel approach is provided for noninvasive diagnosis of the kidney cancer, and the significant clinical practical value is achieved.

The invention relates to a general intelligent measurement model construction method based on meta-analysis. The general intelligent measurement model construction method comprises the following steps: acquiring research data of a plurality of intelligent measurements; determining a screening standard to screen the research data to obtain analysis data, and constructing an analysis data set; performing meta-analysis on the analysis data set to obtain a time weight, a complexity weight and a return weight of the analysis data; constructing a return model and a complexity model of the intelligent measurement; and constructing a universal intelligent measurement model by using the time weight, the complexity weight, the return weight, the return model and the complexity model. According to the invention, heterogeneous intelligent agent measurements of humans, machines, enterprises, governments, institutions and the like are effectively combined; and the relationship among factors such astime, complexity and return of the intelligent measurement is considered, and the existing research data is used for carrying out meta-analysis to obtain the weight of each factor in the intelligent measurement, so that a quantifiable universal intelligent measurement model with higher accuracy is constructed.

The embodiment of the invention provides a drug curative effect multi-index evaluation method based on a Bayesian network and a three-dimensional mathematical model. The method comprises the followingsteps: firstly, acquiring original experimental data of an evaluation drug according to a preset template, and preprocessing the original experimental data to obtain final experimental data for evaluation; carrying out heterogeneity analysis on the final experimental data, and respectively processing the final experimental data based on heterogeneity to obtain a Meta analysis evidence relation graph; calculating the relative sorting of the drug efficacy based on a multi-dimensional Bayesian model, and obtaining the area value under the cumulative sorting probability graph according to the relative sorting; and finally, performing multi-dimensional clustering on the drug efficacy based on the area value under the cumulative sorting probability graph to finish classification of the drug efficacy. According to the technical scheme, the blank in the aspect of drug efficacy evaluation based on a Bayesian method and clustering analysis under multi-outcome indexes is filled up, so that the evaluation and classification result of the drug efficacy is more accurate and more referential.

The invention relates to an application of carbonic anhydrase IV to preparing a lung adenocarcinoma diagnostic preparation. Meta analysis is performed on high-throughout transcriptome data of the lung adenocarcinoma to obtain a differential expression gene, and an analysis tool is applied to analyzing functions of the differential expression gene, so that a candidate gene is screened, and the correlation between the carbonic anhydrase IV and the lung adenocarcinoma is verified by applying a classical molecular biological method; the carbonic anhydrase IV can be used for preparing an auxiliary lung adenocarcinoma diagnostic preparation, and has an important clinical application value.

The invention relates to an analysis on marker evaluation, in particular to a marker level evaluation method which is higher in accuracy. The marker level evaluation method includes: detecting data of impact factors of each marker in each experimental group in an abnormal control group and a control group under different research conditions, performing meta-analysis for the acquired data, comparing the heterogeneity and significance of the impact factors of each marker under different research conditions, and computing an evaluation index of the level of each marker. The marker level evaluation method is higher in reliability and accuracy and can be used for the fields of environmental monitoring, chemical analysis and the like.

The invention discloses an application of an FOXD4L4 gene in preparing a kit for diagnosing colon cancer. By adopting NCBI GEO data retrieval, genome mRNA expression chip data of five colon cancer cases which meet the requirements and normal people are brought into the study range, Meta analysis on the chip data shows that the FOXD4L4 gene is a difference remarkable gene, compared with normal tissue, the expression of the FOXD4L4 gene in colon cancer tissue is down-regulated, and the conclusion is verified by using a fluorescence real-time quantitative PCR method. On such a basis, the invention further discloses a kit for diagnosing colon cancer and a method for diagnosing colon cancer by using the kit. On one hand, a novel idea is provided to study the molecular mechanism of colon cancer, and on the other hand, a relatively sensitive diagnosis kit is provided for primary colon cancer diagnosis.

The invention discloses an evidence retrieval and collection system and method applied to evidence-based medicine. The evidence retrieval and collection system comprises an evidence collection unit, an evidence chain generation module, a data analysis module, an intelligent learning module, an evidence retrieval unit and a model construction module. The invention further discloses the evidence retrieval and collection method applied to evidence-based medicine. The evidence retrieval and collection method comprises the following steps: A, evidence collection; B, evidence chain generation; C, evidence retrieval; D, data analysis; and E, model construction. According to the invention, case evidences of patients can be fully collected and are combined with historical case evidences retrieved from a Cochrane database; timestamps and geographical location information are added into the collected evidence data through an information adding module to form an evidence chain; corresponding historical case evidences can be quickly retrieved through the Meta analysis module; and keyword retrieval is learned through the intelligent learning module, and a retrieval strategy of the intelligent learning module is learned and analyzed, so the purpose of intelligently making a retrieval strategy after related keywords are input is achieved.

The embodiment of the invention discloses a three-dimensional positioning metallogenic prediction method and system for a concealed ore body. The method comprises the steps that geological informationvariables used for performing concealed ore body metallogenic prediction and a three-dimensional data model of a known ore body are established, a geological space range is divided to perform cubic information unit processing, the geological information variables and spatial position registration data of the known ore body in cubic information units are acquired, and a Meta analysis algorithm isused to calculate and obtain a dominance ratio among the geological information variables; and weight values of the geological information variables on mineralization are determined according to the dominance ratio, a comprehensive evaluation value of each cubic information unit is acquired, and a metallogenic prediction target region is defined. Through the metallogenic prediction method and system, three-dimensional positioning metallogenic prediction precision and ore prospecting effectiveness of the concealed ore body are improved based on Meta analysis, a quantitative result of a processing effect can be given, the problem that research results are inconsistent is effectively solved, and an effective method is provided for objective determination of weights.

The invention discloses a thermal correlation health risk early warning method based on a small spatial scale. The method includes: fitting a temperature-death exposure relationship of each small space region by utilizing a DLNM model and a Meta analysis two-stage analysis method; adjusting an exposure reaction relationship of a region with a relatively small daily mortality rate, screening key vulnerability indexes according to a random forest model, calculating a weight result, calculating a vulnerability index of a small space region, calculating a thermal risk index of the small space region in combination with a thermal exposure risk value, dividing health risk levels, and providing a temperature threshold for health risk early warning; the small space scale data of streets is combined; statistical analysis methods and machine learning methods such as a distribution lag nonlinear model and a random forest regression model are applied. Based on the influence of temperature on crowdhealth, various vulnerability indexes are comprehensively considered, a refined heat-related health risk early warning algorithm is established, implementation of high-temperature heat wave prevention and control measures is facilitated, and the health risk of high-temperature heat waves is effectively reduced.

The invention provides a progressive KPI reward calculation system for petrochemical enterprises, which includes: an accident avoidance reward module, a safe team reward module, an accident feasible reward module, other reward modules, a reward fund management module, a monthly statistics module, a summary analysis module, Parametric Design Module. It considers the various process nodes and details of reward management, and is oriented to different user levels of the enterprise. It is easy to operate and provides an effective tool for improving enterprise management.

The invention discloses a quality-related process monitoring method based on weighted partial mutual information, which belongs to the field of fault diagnosis. The present invention combines partial mutual information and Bayesian weighted fusion, under the supervision of multiple quality indicators, selects process variables that are closely related to quality, models the selected variables through correlation meta-analysis, and obtains a process variable that contains the main information of quality changes. related element. The process data space is divided into two subspaces, and statistics are constructed in the subspaces for fault detection. This method can improve the detection rate of quality-related faults, significantly reduce false alarms, and improve the efficiency of actual industrial processes; this paper The inventive method can effectively extract meaningful information hidden in process variables and quality variables; by constructing statistical indicators in two orthogonal subspaces respectively, faults related to quality can be detected, and interference alarms not related to quality can be reduced at the same time.

The present invention relates to a color sample optimization-based illumination preference degree evaluation index construction method and system. The method comprises the steps of constructing a typical color sample spectral reflectance data set; constructing a full-color gamut typical color sample set; collecting a plurality of current representative illumination preference degree research data, and obtaining the relative spectrum power distribution and the corresponding preference degree ranking data of the used light sources; selecting a plurality of color samples from the above full-color gamut typical color sample set, testing all combination modes of the color samples, and calculating the color gamut volume of the specific color sample combination mode on the light source conditions and aiming at the combination modes; calculating the SPEARMAN correlation coefficients between the calculated color gamut volumes and the corresponding preference degree ranking data, and further solving the comprehensive weighted correlation coefficients for researching the corresponding correlation coefficients according to a meta analysis method; on the basis of maximizing the comprehensive weighted correlation coefficients, determining an optimal color sample combination, and taking the color gamut volume of the combined samples on a to-be-tested light source condition as a final index.

The invention discloses a wetland buffer area water ecological health evaluation method based on trend judgment, which comprises the following steps: S1, judging influence factors based on Meta analysis: setting retrieval keywords, collecting experimental observation data of potential influence factors, obtaining key influence factors of water ecological health through environmental factor correlation analysis, and calculating the weight of the influence factors; s2, collecting index data; s3, establishing a prediction model based on machine learning; and S4, trend judgment: inputting the predicted value of each key influence factor and the influence weight of different influence factor types into the water ecological health evaluation model to obtain the water ecological health condition after n years in the future, and taking the water ecological health condition as the prediction evaluation of the current water ecological health state. According to the method, the influence factors which are high in correlation and sensitive in influence can be obtained, limitation caused by regional scale research is eliminated to the maximum extent, the current water ecology health is evaluated from the future perspective, and the development trend of the current water ecology health state and the current state can be better reflected.

The invention relates to an analysis on marker evaluation, in particular to a marker level evaluation method which is higher in accuracy. The marker level evaluation method includes: detecting data of impact factors of each marker in each experimental group in an abnormal control group and a control group under different research conditions, performing meta-analysis for the acquired data, comparing the heterogeneity and significance of the impact factors of each marker under different research conditions, and computing an evaluation index of the level of each marker. The marker level evaluation method is higher in reliability and accuracy and can be used for the fields of environmental monitoring, chemical analysis and the like.