Tempus Labs had five patents in internet of things during Q4 2023. Tempus Labs Inc filed a patent for a method that uses electrocardiogram trace data and clinical data to determine the risk of cardiology diseases in a patient. The method involves a trained machine learning model that evaluates the data for diseases such as cardiac amyloidosis, aortic stenosis, and mitral regurgitation, among others. The model generates a composite risk score indicating the likelihood of the patient being diagnosed with one or more of these diseases within a specific time frame. GlobalData’s report on Tempus Labs gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
Tempus Labs grant share with internet of things as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Ecg-based cardiovascular disease detection systems and related methods (Patent ID: US20230343464A1)
See Also:
Tempus Labs Inc. has developed a method for determining cardiology disease risk by analyzing electrocardiogram trace data and clinical data using a trained machine learning composite model. This model evaluates data related to various cardiology diseases such as cardiac amyloidosis, aortic stenosis, and mitral regurgitation to generate a composite risk score indicating the likelihood of the patient being diagnosed with these diseases within a specific timeframe. The output of this analysis is provided to memory or display for further action. The patent also includes claims detailing the process of evaluating electronic health data for a subject, generating clinical scores, identifying monitoring or management procedures based on the scores, and sending reports to recipients including the recommended procedures.
The method involves multiple layers of a machine learning model to process electronic health data, generate clinical scores, and provide notifications if certain thresholds are exceeded. The system and computer-readable medium described in the patent aim to streamline the evaluation process by utilizing data from different sources, including electrocardiogram trace data, vitals, laboratory results, and comorbidities. Additionally, the patent outlines the importance of training the machine learning model on diverse subject populations to ensure accurate predictions and the ability to modify the model based on demographic characteristics. Overall, Tempus Labs Inc.'s patent focuses on leveraging advanced technology to assess cardiology disease risk efficiently and provide personalized recommendations for monitoring and managing potential health issues.
To know more about GlobalData’s detailed insights on Tempus Labs, buy the report here.
Premium Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
