Cigna Group has been granted a patent for a computerized confidence interval determination system. The system uses historical data and machine learning to generate predictions and confidence intervals in response to user requests, ensuring accuracy and reliability in decision-making processes. GlobalData’s report on Cigna Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Cigna Group, Social media analytics was a key innovation area identified from patents. Cigna Group's grant share as of May 2024 was 44%. Grant share is based on the ratio of number of grants to total number of patents.
Confidence interval determination system using historical data for predictions
A recently granted patent (Publication Number: US12001928B1) discloses a computerized confidence interval determination system that utilizes historical data to provide accurate predictions. The system, comprising at least one processor and memory, stores training data related to a specific category and previous prediction requests. Upon receiving a prediction request, the system compares elements of the request to historical data, determining matches and changes in training data. Based on this analysis, the system generates predicted likelihoods, mean vector predictions, and covariance matrices to determine outcomes and confidence intervals. If the confidence interval exceeds a threshold, the predicted outcome and interval are outputted to the user device.
Furthermore, the patent includes a method for confidence interval determination that follows a similar process as the system. By analyzing the size of each element in a prediction request, comparing it to historical data, and generating updated classifiers based on training data, the method calculates predicted likelihoods and confidence intervals. The method also involves generating mean vector predictions and covariance matrices based on the set of predicted likelihoods for each element of the prediction request. This innovative approach aims to enhance prediction accuracy and provide users with reliable confidence intervals for decision-making processes.
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