849 results about "Predictive value" patented technology

The invention provides a method for predicting which network objects are likely to be requested by a web user from a web server, such as that used in conjunction with an internetworking environment. A request made by a web user for a web object is parsed and dynamic values contained therein normalized. A prediction is made based on the normalized request, statistical measures, and other factors about what other web objects the web user is likely to request. The predictive information is then made available to the web server and the predicted net objects are pre-downloaded to the Web client. A pre-download statistics server may be used to record and provide statistics to assist in the prediction process. Examples described herein relate to web pages, but the invention is broadly applicable to many different types of requests for information (such as, for example, database queries and other libraries of information.)

Methods, systems, and computer program products for developing and using predictive models for predicting medical outcomes and for evaluating intervention strategies, and for simultaneously validating biomarker causality are disclosed. According to one method, clinical data from different sources for a population of individuals is obtained. The clinical data may include different physical and demographic factors regarding the individuals and a plurality of different outcomes for the individuals. Input regarding a search space including models linking different combinations of the factors and at least one of the outcomes is received. In response to receiving the input, a search for models in the search space based on predictive value of the models with regard to the outcome is performed. The identified models are processed to produce a final model linking one of the combinations of factors to the outcome. The final model indicates a likelihood that an individual having the factors in the final model will have the outcome.

The present invention provides a means for guiding a medical device within the body to approach a target destination. The system and method provide a means for determining a predicted length and orientation, navigating the device to an intermediate point less than the predicted length, determining an error between the projected destination and actual target destination, and successively updating a predicted value of a control variable to yield an orientation within a predetermined distance error before advancing the device the remaining distance to the destination. This provides a physician with the capability of verifying the device will be accurately guided to the target destination without trial and error. A method is also provided for intuitive navigation to targets with limited trial and error based on user-applied device orientation adjustments, where the user chooses the magnitude of the adjustments and the system determines the adjustment direction.

A computerized method includes analyzing data associated with a credit line during an origination stage for predictive variables for use in a model for first party fraud, and flagging an account during the origination stage when at least one or more predictive origination stage variables cause a model score to exceed a pre-defined fraud likelihood threshold. The computerized method also includes analyzing data associated with one or more previously flagged, post-booked stage credit lines for data elements or transactions to be used as variables in a model to predictive of first party fraud at the customer-level or in one or more of the post-booked stage credit lines.

The statistical analysis described and claimed is a predictive statistical tree model that overcomes several problems observed in prior statistical models and regression analyses, while ensuring greater accuracy and predictive capabilities. Although the claimed use of the predictive statistical tree model described herein is directed to the prediction of a disease in individuals, the claimed model can be used for a variety of applications including the prediction of disease states, susceptibility of disease states or any other biological state of interest, as well as other applicable non-biological states of interest. This model first screens genes to reduce noise, applies k-means correlation-based clustering targeting a large number of clusters, and then uses singular value decompositions (SVD) to extract the single dominant factor (principal component) from each cluster. This generates a statistically significant number of cluster-derived singular factors, that we refer to as metagenes, that characterize multiple patterns of expression of the genes across samples. The strategy aims to extract multiple such patterns while reducing dimension and smoothing out gene-specific noise through the aggregation within clusters. Formal predictive analysis then uses these metagenes in a Bayesian classification tree analysis. This generates multiple recursive partitions of the sample into subgroups (the “leaves” of the classification tree), and associates Bayesian predictive probabilities of outcomes with each subgroup. Overall predictions for an individual sample are then generated by averaging predictions, with appropriate weights, across many such tree models. The model includes the use of iterative out-of-sample, cross-validation predictions leaving each sample out of the data set one at a time, refitting the model from the remaining samples and using it to predict the hold-out case. This rigorously tests the predictive value of a model and mirrors the real-world prognostic context where prediction of new cases as they arise is the major goal.

A computer-aided diagnostic method and system provide image annotation information that can include an assessment of the probability, likelihood or predictive value of detected or identified suspected abnormalities as an additional aid to the radiologist. More specifically, probability values, in numerical form and / or analog form, are added to the locational markers of the detected and suspected abnormalities. The task of a physician using such a system as disclosed is believed to be made easier by displaying markers representing different regions of interest.

A method for a first computer to request documents from a second computer includes steps of sending a first request for a first document to the second computer responsive to a first user action, receiving the first document sent by the second computer responsive to the first request; identifying all references to second documents in the received first document; independently of any user action, automatically sending a second request for at least one of the second documents referred to by the identified references; receiving the second document(s) requested by the second request and storing the received second document(s) in a storage that is local to the first computer, and responsive to a user request for one or more of the second documents, attempting first to service the user request from the local storage and sending a third request to the second computer for second document(s) only when the second document(s) is not stored in the local storage. A method of servicing a request for access to a Web site by a remote computer may include a receiving step to receive the request for access to the Web site; a first sending step to send a first page of the accessed Web site to the remote computer responsive to the request, and independently of any subsequent request for a second page of the Web site originating from the remote computer, preemptively carrying out a second sending step to send the remote computer at least one selected second page based upon a prediction of a subsequent request by the remote computer and / or a history of second pages previously accessed by the remote computer.

A computer-aided diagnostic method and system provide image annotation information that can include an assessment of the probability, likelihood or predictive value of detected or identified suspected abnormalities as an additional aid to the radiologist. More specifically, probability values, in numerical form and / or analog form, are added to the locational markers of the detected and suspected abnormalities. The task of a physician using such a system as disclosed is believed to be made easier by displaying markers representing different regions of interest.

Methods and systems utilizing the data provided by a non-contrast-enhanced CAC scan that is left unused by the “whole-heart” Agatston or volume scores. Agatston and volume scores summarize overall coronary calcium burden, but do not show the number of vessels involved, the geographic distribution of the lesions, the size and shape of the individual lesions and the distance of the lesions from the coronary ostium. The methods and systems described herein extract and use the enhanced information provided by 3-D CAC scan data and significantly increases its clinical predictive value by providing vessel and lesion specific CAC scores which are superior to the whole-heart Agatston and volume scores in predicting obstructive Coronary artery disease (CAD).

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing predictive pre-recording of audio for voice input. In one aspect, a method includes establishing, as input data, state data that references a state of a mobile device and sensor data that is sensed by one or more sensors of the mobile device, applying a rule or a probabilistic model to the input data, inferring, based on applying the rule or the probabilistic model to the input data, that a user of the mobile device is likely to initiate voice input, and invoking one or more functionalities of the mobile device in response to inferring that the user is likely to initiate voice input.

Disclosed are methods and data on determining response to a drug or other therapy prior to administration by obtaining a direct neurocognitive brain function measurement; obtaining an indirect neurocognitive brain function measurement; and, assessing the direct neurocognitive brain function measurement and the indirect neurocognitive brain function measurement collectively to obtain a response determination preferably the predictive value of the collective assessment is greater than a predictive value obtained from the separate predictive values for the direct and indirect measurements. Also disclosed are methods of determining dosage of a drug comprising administering a drug; comprising obtaining a direct neurocognitive brain function measurement; obtaining an indirect neurocognitive brain function measurement; and, assessing the direct neurocognitive brain function measurement and the indirect neurocognitive brain function measurement collectively to obtain a dosage, preferably the predictive value of the collective assessment is greater than a predictive value obtained from the separate predictive values for the direct and indirect measurements; optionally, additional cycles of obtaining and assessing indirect and direct measurements are performed.

A system and method, in the context of a search engine marketing campaign, for determining a value to be placed upon at least one mode through which an Internet user is referred to or otherwise enters a website of interest is described. Several embodiments include systems and methods for valuing at least one referral mode based on data acquired from one or more search engines and / or web analytics tools. The systems and methods are further configured to perform fraud analysis, achieve a predictive value of a referral mode and / or optimize the placement of a website in organic or paid search results at one or more search engines based on the value of the at least one referral mode.

Methods and systems for performing comprehensive predictive analysis and modeling in a wager gaming environment are provided. Statistical calculations for deriving predictive values for a patron behavior in a casino or gaming environment may include various criteria, including but not limited to wager gaming activities, resort / hotel usage, dining / meals, non-gaming point of sale transactions, entertainment expenditures, coupon / prize redemption, “comps” provided, etc. In some implementations, a plurality of predictive models may be used. One or more criteria may be used to evaluate and / or rank the predictive models. For example, such an evaluation and / or ranking may be based, at least in part, on a correlation coefficient or a function thereof. In some such implementations, an evaluation and / or ranking may be based, at least in part, on a comparison of the coefficient of determination, R2, corresponding to each predictive model.

The invention discloses a self-adaptation three-dimensional attitude positioning method based on microinertia and a geomagnetic technology, comprising the following steps of: (1) inducing a motion attitude of a carrier by utilizing a sensor of a microinertia measuring device; (2) setting an initial attitude of the microinertia measuring device and accelerated speed and geomagnetic field information under a global coordinate system; (3) solving the attitude value of the microinertia measuring device; (4) predicting the attitude value of the microinertia measuring device by utilizing triaxial micro-gyroscope sensor data; (5) carrying out confidence judgment on the triaxial micro-acceleration sensor data and triaxial magnetic field sensor data, detecting the interference of a surrounding environment, and setting self-adaptation parameters; (6) obtaining the attitude error value of the microinertia measuring device by utilizing the triaxial micro-acceleration sensor data and the triaxial magnetic field sensor data which are processed in the step (5); (7) fusing the attitude predictive value obtained from the step (4), corrected information obtained from the step (6) and the self-adaptation parameters obtained from the step (5) to obtain the attitude value of the microinertia measuring device; and (8) outputting attitude information.

The invention discloses a state monitoring and failure diagnosis method for a wind generating set variable pitch system. The method includes the steps that 1, in data collection, operation parameters related with the operation state of the variable pitch system are extracted from a wind generating set SCADA system; 2, according to feature parameter extraction, a Relief algorithm is utilized for extracting effective feature parameters of the variable pitch system; 3, in data analysis and prediction, historical data during normal operation of the variable pitch system are screened out to establish a health model of a fan and calculate the prediction value of a real-time signal and the difference between an actual output value and the prediction value; 4, according to a diagnosis algorithm, the operation state of the fan is judged according to residual error information transmitted by the step 3, and the main failure reason of the variable pitch system is found according to a corresponding diagnosis rule and the contribution rate of residue errors; 5, according to data storage, real-time data, prediction data and the diagnosis result are stored to facilitate failure analysis at the later period and provided as reference data for modifying the failure diagnosis rule.

The predictive asset ranking system and process quantifies the condition of major components and sub-components of a property based on a systematic comparison of one major component against another utilizing analytical hierarchy analysis. The predictive asset ranking may be expressed as a value or score that may be used as a benchmark to compare one property to another property. The predictive asset ranking process applies multiple analytical hierarchies to the various attributes of a property. The analytical hierarchy may be based on an attribute weighing process and may include a series of qualitative questions indicative of attributes of the property. The predictive asset ranking system may be dynamic and may be customized for the particular asset being evaluated. When the system is customized, the process may automatically recalculate the weights and redistribute the points used in the predictive asset ranking analysis.

A plurality of ECG Superscore formulae, created from multiple parameter ECG measurements including those from advanced ECG techniques, can be optimized using additive multivariate statistical models or pattern recognition procedures, with the results compared against a large database of ECG measurements from individuals with known cardiac conditions and / or previous cardiac events. Superscore formulae utilize multiple ECG parameters and accompanying weighting coefficients and allow data obtained from any given patient to be used in calculating that patient's ECG Superscore results. ECG Superscores have retrospectively optimized accuracy for identifying and screening individuals for underlying heart disease and / or for determining the risk of future cardiac events. They thus have greater predictive value than that of any conventional or advanced ECG measurement alone or of any non-optimized combinations of conventional or advanced ECG measurements that have been used in the past. Ongoing optimization of ECG Superscore diagnostic and predictive accuracy may be realized through the iterative adjustment of Superscore formulae based on the incorporation of data from new patients into the database and / or from longitudinal follow-up of the disease and cardiac event status of existing patients.

An improved system and method is provided for sparse Gaussian process regression using predictive measures. A Gaussian process regressor model may be construction by interleaving basis vector set selection and hyper-parameter optimization until the chosen predictive measure stabilizes. One of various LOO-CV based predictive measures may be used to find an optimal set of active basis vectors for building a sparse Gaussian process regression model by sequentially adding basis vectors selected using a chosen predictive measure. In a given iteration, a predictive measure is computed for each of the basis vectors in a candidate set of basis vectors and the basis vector with the best predictive measure is selected. The iterative addition of basis vectors may stop when predictive performance of the model degrades or no significant performance improvement is seen.

A lightweight document matcher employs minimal processing and storage. The lightweight document matcher matches new documents to those stored in a database. The matcher lists, in order, those stored documents that are most similar to the new document. The new documents are typically problem statements or queries, and the stored documents are potential solutions such as FAQs (Frequently Asked Questions). Given a set of documents, titles, and possibly keywords, an automatic back-end process constructs a global dictionary of unique keywords and local dictionaries of relevant words for each document. The application front-end uses this information to score the relevance of stored documents to new documents. The scoring algorithm uses the count of matched words as a base score, and then assigns bonuses to words that have high predictive value. It optionally assigns an extra bonus for a match of words in special sections, e.g., titles. The method uses minimal data structures and lightweight scoring algorithms to compute efficiently even in restricted environments, such as mobile or small desktop computers.

A computer-aided diagnostic method and system provide image annotation information that can include an assessment of the probability, likelihood or predictive value of detected or identified suspected abnormalities as an additional aid to the radiologist. More specifically, probability values, in numerical form and / or analog form, are added to the locational markers of the detected and suspected abnormalities. The task of a physician using such a system as disclosed is believed to be made easier by displaying markers representing different regions of interest.

The invention discloses a short-term wind power prediction method based on integrated empirical mode decomposition and a deep belief network. The short-term wind power prediction method comprises the steps of: decomposing an original wind power sequence into a series of intrinsic mode functions with different features by adopting integrated empirical mode decomposition, calculating sample entropy of the original wind power sequence and the intrinsic mode functions, combining the intrinsic mode functions with similar sample entropy values into a new sequence, and forming a random component, a detail component and a trend component; selecting an input variable set by adopting a partial autocorrelation function; constructing a training sample set according to the input variable set of each component; and establishing a deep belief network short-term wind power prediction model for each component, and superposing prediction results of the components, so as to obtain a final short-term wind power predicted value. The short-term wind power prediction method provided by the invention effectively improves the short-term wind power prediction precision, and can effectively solve the wind power prediction problem of the electric power system, so as to provide more reliable guarantee for large-scale wind power integration.

In vitro culture devices and methods are described. The subject methods and devices provide a means whereby cells and / or subcellular material are grown or held in a culture device that maintains the cells and / or subcellular material in a physiologically representative environment, thereby improving the predictive value of toxicity and metabolism assays, and the relevance of experimental results derived from such assays to actual in vivo conditions, processes and outcomes. The culture devices of the invention comprise a fluidic channel connected to or otherwise integrated with at least one chamber, preferably integrated in a chip format. The specific chamber geometry is designed to provide cellular interactions, liquid flow, and liquid residence and other parameter values that correlate with those found in or produced by the corresponding cell, organs or tissues, or components or products thereof, in vivo. Each device comprises at least one chamber and at least one inlet and one outlet port that allow for recirculation of the culture medium. The device will usually include a mechanism for obtaining signals from the cells and culture medium.

The present invention applies classical survival analysis to genome-wide gene expression profiles of prostate cancers and preoperative prostate-specific antigen levels from prostate cancer patient, to identify prognostic markers of disease relapse that provide additional predictive value relative to prostate-specific antigen concentration. The present invention provides a method of determining prognosis of prostate cancer and predicting prostate cancer outcome of a patient. The method comprises the steps of first establishing the threshold value of at least one prognostic gene of prostate cancer. Then, the amount of the prognostic gene from a prostate tissue of a prostate cancer patient is determined. The amount of the prognostic gene present in that patient is compared with the established threshold value of the prognostic gene, whereby the prognostic outcome of the patient is determined.

We analyzed bone marrow from 67 patients from a phase 2 study of farnesyltransferase inhibition with tipifarnib (R115777, ZARNESTRA®), in older adults with previously untreated, poor-risk acute myeloid leukemia (AML) for N-Ras mutations, global gene expression, and / or quantitative PCR (qPCR) of specific genes. Microarray profiling identified a two-gene expression ratio (RASGRP1:APTX) which provided the greatest accuracy for predicting response to tipifarnib. We demonstrated that this classifier could predict response to tipifarnib in an independent set of 54 samples from relapsed or refractory AML, with a NPV and PPV of 92% and 28%, respectively (odds ratio of 4.4). Therefore, in both newly diagnosed and relapsed or refractory AML, this classifier improves the overall response rate by approximately 50% while maintaining a high NPV, and significantly improves patient overall survival. The two-gene classifier was also validated by qPCR in thirty AML samples from the same clinical study demonstrating a negative predictive value (NPV) and positive predictive value (PPV) of 81% and 50%, respectively (odds ratio of 4.3). These data indicate that a simple two-gene expression assay may have utility in diagnosing a population of AML patients who are more likely to respond to tipifarnib.

The invention discloses a method and a device for encoding and decoding a video. The method comprises the following steps: in a reference frame with the same direction, determining a reference image block in a remote reference frame corresponding to a current encoding image block; and according to a motion vector of the remote reference image block, calculating a motion vector of an adjacent reference image block corresponding to the current encoding image block, obtaining the corresponding adjacent reference image blocks; and then according to the adjacent reference image blocks and the remote reference image blocks, calculating and determining the predicted value of the current encoding image block based on the mote reference image block; finally carrying out encoding operation according to the predictive value based on the remote reference image block. The decoding end adopts the corresponding decoding strategy to carry out the decoding operation. By using the embodiment of the invention, more precise predictive value of the current encoding image block based on the remote reference block can be obtained, thereby the load of the code stream can be effectively reduced under the condition that the complexity of searching the motion vector is not increased.

There are provided an image coding method and apparatus which can properly reduce the computation cost required for rate / distortion optimization processing in image coding at the time of image compression. First of all, the rate / distortion gradient of a frame of interest is classified to m categories. A category information creating unit (101) acquires a threshold λ for a preceding frame from a predictive value storage unit (104) as a predictive value λ′ for the frame of interest when the frame of interest is to be coded, and further finely segments a category in which the predictive value λ′ is included. A code amount is then calculated for each of n categories in which the predictive value λ′ is included. A code sequence forming unit (103) selects a category having a target rate, and searches for a threshold between an upper limit value Tn(x-1) and lower limit value Tn(x) of the category. S at the end of the processing is selected as the threshold λ, and a code sequence is formed by using the threshold λ.

A method and system is used to construct a forecast error confidence interval. The predication interval provides a range of error for a current forecast value to any desired confidence level. The method and system involve running a forecast method on a set of historical data. For each historical period, a forecast is obtained at each time point in the period. The forecasts are compared to the target value of interest in each period. The comparison of target values to forecast values is used to build an error series for each historical period. The error values within each error series are pooled to form an error distribution series. The error distribution series can be used to provide a confidence interval for the current forecast.