42 results about "Demographic statistics" patented technology

Exemplary embodiments of the present invention provide a method of health insurance market risk assessment including receiving first data including demographic and cost data for members of a health insurance plan in a current market, receiving second data including demographic data for the current market, and receiving third data including demographic data for a new market. The first to third data are used to transform a distribution of the plan members to account for differences between the current and new market demographic data and to estimate probabilities of enrollment in the new market. A statistical model is learned to predict risk in the new market using the transformed distribution and the estimated probabilities. The statistical model is used to determine risk of entering the new market.

The invention discloses a deforming statistical map based multi-view spatio-temporal data visualization method and application. Spatio-temporal data having geography and time attributes is visualized by adopting a method of multi-view and multi-tag mixed layout formed by combining a traditional map, a statistical map, time axis and a pie chart, a bar graph, a bubble chart and a Nightingale rose diagram in a statistical chart, and the dissymmetry problem of data distribution and space utilization of a traditional map visualization method and the problem that the attributes of multi-dimensional data display are not comprehensively displayed are avoided. A user can be helped to understand all the aspects of data from multiple perspectives, meanwhile a classic visualized statistic analysis chart, the map time axis and the like are combined, so that data display is specific and vivid. The deforming statistical map based multi-view spatio-temporal data visualization method can be applied to the fields of data visualization of microblogs, WeChat, demographic statistics, infectious disease distribution, elector distribution and the like, and visualization and visual analysis conducted on the data having the time relation of spatial distribution are achieved.

The invention discloses a sepsis early prediction method based on machine learning. The method comprises the following steps: firstly, extracting clinical data, including demographic statistics (suchas age and gender), vital sign variables (such as heart rate and systolic pressure) and laboratory measurement indexes (such as creatinine and platelet count), of a patient within 24 hours after a patient enters an ICU by utilizing an electronic medical record, preprocessing the data, inputting the preprocessed data into an improved deep forest algorithm model for training, and outputting the disease probability of the patient after training optimization. And meanwhile, the algorithm model can also sort characteristic variables and output an early warning factor which has great influence on early prediction of sepsis. Finally, corresponding variables of the patient needing to be predicted are input into the trained model, so that early prediction of sepsis can be carried out on the patient. According to the invention, early prediction is carried out on sepsis based on a machine learning method, doctors can be assisted in making clinical decisions, and the prediction accuracy is improved.

The invention discloses a demographic statistics device and method based on boundary selection, and belongs to the field of deep learning and image processing. The invention comprises the following steps of by improving the YOLO neural network by increasing the division of the YOLO unit from 7*7 to 9*9, that is, increasing the number of detections per unit to three, and then replacing the YOLO PCneural network with the Fire module in SqueezeNet; replacing The 16th, 18th, and 24th 3*3 convolutional layers with Dire modules in SqueezeNet and decreasing the number of compressed portion of the Fire module from 128 to 96; retraining network to get a new S-YOLO-PC neural network, using the S-YOLO-PC neural network for boundary selection of human flow statistics, using the new neural network, making it more accurate in the case of greatly reduced models, can be used in a variety of occasions Human flow detection.

A contiguous cartogram is distorted proportionally to demographic data associated with geographical areas. The cartogram is associated with an underlying data set (such as health indication data or epidemiological data) that is geographically smoothed to avoid meshing and border effects, and shaded according to a predetermined shading scale. The cartogram may be stacked with other cartograms associated with underlying data sets collected at different times to form a chronological cartogram slideshow to illustrate changes in the underlying data set over time. The chronological cartogram slideshows may be transmitted from a map server via a communications interface to a requesting client.

The invention discloses a disease risk analysis system based on a pathological mode and an attention mechanism, wherein the system comprises an information collection device and a server; the information collection device is in communication connection with the server; the information collection device transmits the acquired demographic characteristic data information of a plurality of patients and the acquired electronic medical record data information of a target disease to the server; a portrait construction module, a graph embedding algorithm module, a medical record information extractionmodule, a training set construction module, a decision tree integration model module, a vectorization module, an attention mechanism module, a representation vector calculation module, a splicing module and a logistic regression analysis module are arranged in the server, and the server obtains a result required by health early warning based on the modules. According to the invention, big data service support is provided for health early warning, and the system has the advantage of accurate analysis result.

The invention provides a two-stage passenger crowd travel purpose analysis method integrating bus data and POI data, aims to solve the problem of identifying bus passenger crowd travel purposes by combining the bus data and the POI data, and provides a novel, reasonable and effective passenger crowd travel purpose analysis method. The method mainly comprises two stages, in the first stage, firstly, the bus data and the POI data are extracted, cleaned and converted, station information is converted into POI vectors, and finally, a clustering method is adopted to analyze the travel purpose of bus passengers; in the second stage, firstly, card swiping data and intelligent card data are combined to extract the demographic information of passengers, then the riding distance of the passengers iscalculated, the travel purpose of the first stage is used as the characteristics of passenger group clustering, and finally, a clustering algorithm is used for clustering passengers, and the travel purpose in each cluster is analyzed, so that the effect of analyzing different travel purposes of different riding crowds is achieved. The method is used for analyzing the travel purpose of the publictransport passenger crowd.

The embodiment of the invention provides a population data statistics method and device, computer equipment and a readable storage medium, and relates to the technical field of population statistics,and the population data statistics method comprises the steps: obtaining initial land image data and signaling data of a plurality of target types, wherein one piece of signaling data of the target type corresponds to one population feature; constructing a uniform grid layer according to the initial land image data, wherein the uniform grid layer comprises a plurality of uniform grid surfaces, andeach uniform grid surface at least intersects with any one to-be-measured area in the plurality of to-be-measured areas; according to the plurality of uniform grid surfaces, constructing and obtaining an undetermined position relationship between each region to be measured and the signaling data of each target type; and according to the undetermined position relationship, performing statistics toobtain population data of each to-be-tested area. Through the steps, population statistics can be efficiently achieved.

Disclosed is a system and method to collect data from a plurality of data sources to quantify the sentiment of users and predict objective outcomes. The method includes the step of collecting sentiment data from the first data sources associated with the user to determine an opinion of the user pertaining to products, and services through a sentiment analysis module. The method includes the step of collecting action data from the second data sources associated with the user to determine the behavior of the user through a behavioral analysis module. The second data sources include social media platforms, digital shopping platforms, and native applications. The method includes the step of collecting demographic data of the user from the third data sources to determine the profile of the user through a demographic profiling module. The third data source comprising a telecom server. The method includes the step of storing and analyzing data pertaining to the determined opinion of the user, determined behavior of the user, and determined profile of the user and computing a user profile value through a server. The method includes the step of presenting a persistent view of the analyzed data corresponding to the user through a user interface connected to a central computing device that configures the server with the telecom server.

The invention provides a method for judging the number of one-machine multi-card users in regional population based on track similarity. The method comprises: randomly extracting a certain number of IMSIs from resident population of a residence place in a statistical area, and determining a moving track of each IMSI according to the number of base stations accessed by each IMSI in the sampling data in a statistical time period and the residence time of each IMSI in each base station; comparing the moving tracks of one IMSI with the moving tracks of other IMSIs one by one, and screening out candidate one-machine multi-card users; and checking the candidate one-machine multi-card users by adopting hypergeometric distribution, carrying out multiple correction on a checking result, and judgingone-machine multi-card users in the sampling data. The method is used for carrying out regional demographic statistics through mobile big data, and the demographic statistics result is corrected by using the judged one-machine multi-card user in the statistical region, so that the demographic statistics accuracy can be improved.

A computer implemented method for determining demographic information to facilitate mobile application user engagement in a remote computing environment is provided. The method includes capturing and compiling social media data for a user into a first database; processing the social media data by detecting explicit identifications of demographic attributes of the user; setting a probability value of 100% for each explicitly identified demographic attribute for a category; setting a probability value of 0% for each demographic attribute not explicitly identified for the category; determining a derived attribute for a second category by searching a secondary database using the explicitly identified demographic attribute; training a neural network using training data, the training data comprising the explicitly identified demographic attribute and its associated probability value, and the derived attribute and its associated probability value; inputting, to the neural network, social media data of a second user; predicting, by the neural network, demographic attributes of the second user.

The invention provides an intelligent oxytocin dosage regulation and control method based on uterine contraction signals and LightGBM, and the method comprises the steps: obtaining the uterine contraction signals, carrying out the preprocessing, and further carrying out the feature extraction based on the uterine contraction intensity; obtaining characteristic variables with statistical significance and time-of-birth physiological parameters to form data characteristic items; according to the data feature items, combining the demographic data and the intranatal physiological parameter data toobtain initial sample data, and screening out model input data from the initial sample data in combination with the uterine contraction signals subjected to feature extraction; constructing a time-producing oxytocin dosage prediction model based on a LightGBM algorithm of Bayesian optimization; importing the model input data into a time-production oxytocin dosage prediction model for calculation to obtain a numerical value corresponding to a final oxytocin dripping speed change condition. By implementing the invention, the contradiction between the dependence of the traditional infusion schemeon personal experience and the shortage of human resources of medical personnel can be overcome, the labor cost is reduced, and the precise oxytocin dosage intelligent regulation and control is realized.

The invention discloses clinical diagnosis and treatment application of acute ischemic stroke based on cerebral microhemorrhage detection. The application comprises: selection of a research object, which specifically comprises the following steps: continuously selecting acute ischemic stroke patients hospitalized and treated in the neurology department of the second affiliated hospital of the Xuzhou Medical University from October 2016 to February 2017 as the research object by adopting a prospective research design, collecting and sorting clinical data such as demographic statistics, vascularrisk factors, imaging examination, laboratory examination and treatment modes of patients, and dividing the patients into a CMBs group and a CMBs-free group according to whether the patients are accompanied by CMBs or not; when follow-up visit is carried out for 6 months after attack, dividing the patients in the CMBs group and the patients in the CMBs-free group into a subgroup with poor prognosis (mRS score=2) and a subgroup with good prognosis (mRS score is 0-2) according to an improved Rankin scale (mRS) score; applying single-factor analysis and multi-factor Logistic regression analysisto screen out influence factors of poor prognosis of the patient.

A method of generating demographic statistics related to an event includes using sensor data acquired at a mobile device to estimate a value for a category of a demographic model of a user of the mobile device; using sensor data acquired at the mobile device to detect an occurrence of the event in which the user of the mobile device participates; and associating the estimated value for the category of the demographic model of the user of the mobile device with the event.

The invention belongs to the technical field of population density estimation, and discloses an urban characteristic block population density estimation method and system based on spatial big data. The urban characteristic block population density estimation system based on the spatial big data comprises a remote sensing image acquisition module, a population information acquisition module, a main control module, an image recognition module, a population statistics module, a population density calculation module, a simulation module, a cloud storage module and a display module. According to the invention, through the population information acquisition module, the staff management work required for floating population information acquisition by a floating population management department is saved, and no special population information acquisition equipment needs to be purchased, so the cost is saved; meanwhile, the population density condition of the prefecture-level city-level cities can be effectively simulated through the simulation module, manual statistics is replaced with an automatic means, and a large amount of manpower and material resources can be saved.