Stryker had 19 patents in artificial intelligence during Q1 2024. Stryker Corp’s patents filed in Q1 2024 include a computer-implemented technique for selecting a machine-trained model to determine implant-related parameters based on patient anatomy, a method for recommending inpatient or outpatient surgery based on patient data, a system for aiding in positioning surgical objects in a surgical environment using machine vision, a method for estimating blood loss in a fluid canister, and a system architecture for real-time processing and displaying of medical imaging data with reduced latency. GlobalData’s report on Stryker gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Stryker grant share with artificial intelligence as a theme is 26% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Technique for selecting a machine-trained model for determining an implant-related parameter (Patent ID: US20240104727A1)
The patent filed by Stryker Corp describes a computer-implemented technique for the user-specific selection of a machine-trained model to determine implant-related parameters based on patient anatomy. The method involves receiving patient image data, applying machine-trained models to determine parameters, suggesting these parameters to the user, receiving feedback, and selecting subsequent models based on user input. The models are selected based on historical data associated with the user and can be adapted based on user feedback, auxiliary information, and user input regarding the specific area of treatment, such as vertebrae in the spine.
Additionally, the patent outlines a method for machine-training different models based on training data from various users related to specific patient anatomies. The training data is divided into classes based on implant-related parameters, and the models are trained accordingly. The training process can be manual or automatic, utilizing similarity metrics or cluster analysis. The apparatus described in the patent is configured to implement these methods, providing a user-specific selection of models for determining implant-related parameters and machine-training models based on training data from multiple users.
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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.
