UnitedHealth Group had 47 patents in artificial intelligence during Q2 2024. The patents filed by UnitedHealth Group Inc in Q2 2024 focus on generating predicted recommendations using collaborative filtering machine learning models, training machine learning models with natural language rules, improving resource allocation based on non-linear causal effect predictions, predicting the next text based on document processing and machine learning models, and revising classifier predictions by tokenizing classification labels and using embedding models. GlobalData’s report on UnitedHealth Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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UnitedHealth Group had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Collaborative filter techniques for generating predicted recommendations in sparse domains (Patent ID: US20240212054A1)
The patent filed by UnitedHealth Group Inc. describes a method, apparatus, and system for generating predicted recommendations using input and reference entity representations along with a collaborative filtering machine learning model. The method involves generating an input entity representation based on entity representation features, training the collaborative filtering model on an initialization dataset, and using the model to predict recommendations. These recommendations are then used to perform prediction-based actions, such as generating a recommendation user interface.
Additionally, the patent includes claims for determining qualifying reference entity representation subsets, selecting candidates based on similarity measures and ratings, and generating model-predicted entity-candidate matrices. The computing apparatus and computer program product described in the patent are configured to carry out these methods, including generating input entity representations, training collaborative filtering models, and initiating prediction-based actions based on the predicted recommendations. The patent emphasizes the use of historical data extracted from document data objects to generate the initialization dataset and highlights the importance of generating recommendation user interfaces as part of the prediction-based actions.
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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.
