Becton Dickinson and Co had 27 patents in artificial intelligence during Q2 2024. The patents filed by Becton Dickinson and Co in Q2 2024 include a method for extracting clinically significant data from unstructured clinical data to control medical devices, a wearable device for monitoring tissue swelling conditions, a system for recommending thermal pad sets for targeted temperature management therapy, a peer network for identifying anomalous behavior in clinicians, and vascular access systems with ultrasound monitoring capabilities. GlobalData’s report on Becton Dickinson and Co gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Becton Dickinson and Co had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Machine learning enabled extraction of unstructured clinical data (Patent ID: US20240202595A1)
The patent filed by Becton Dickinson and Co. describes a computer-implemented method that involves receiving unstructured clinical data, applying a machine learning model to identify entities within the data, extracting clinically significant data, and controlling medical devices based on this data. The machine learning model is trained to determine the most likely entity following a given entity in the data, and an entity graph is generated based on the alignment of entities. The method also involves training the model on annotated data to learn entity patterns and performing tasks such as identifying stages of clinical workflows and allocating resources based on the data.
Furthermore, the method includes using second machine learning models to extract clinically significant data, determining the actionability of messages based on the data content, and controlling medical devices by transmitting messages to adjust their operational state or functional elements. The patent also covers the system and computer-readable medium storing instructions for implementing this method. Overall, the patent outlines a comprehensive approach to leveraging machine learning for processing unstructured clinical data, extracting valuable insights, and optimizing the operation of medical devices based on this information.
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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.
