Becton Dickinson and Co had three patents in big data during Q4 2023. The patents filed by Becton Dickinson and Co in Q4 2023 include a method for determining actionable messages from data systems, extracting clinically significant data, and performing tasks such as resource allocation and detecting inefficiencies in clinical workflows. Another patent discloses a system for flow cytometry with a laser, detector, and analysis module for reconstructing an image of a sample. Additionally, a graphical user interface for processing flow cytometer data is described, allowing for group-wise analysis of data, display of compound populations, data gates, and data files, with systems and methods for implementation provided. GlobalData’s report on Becton Dickinson and Co gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

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Becton Dickinson and Co grant share with big data 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: Machine learning based clinical resource controller (Patent ID: US20230402182A1)

The patent filed by Becton Dickinson and Co. describes a method that involves receiving messages from data systems, applying a machine learning model to determine if the message is actionable, extracting clinically significant data from actionable messages, and performing tasks based on this data. These tasks include resource allocation for clinical workflows and detecting inefficiencies. The patent also covers systems that implement this method, including data processors and memory storing instructions for processing messages, determining actionable messages, extracting data, and controlling medical devices based on the data.

The system described in the patent can identify stages of clinical workflows, measure time between stages, and take corrective actions if delays exceed a threshold. It can also allocate resources based on the data extracted from messages, such as antimicrobials for microbes. The machine learning model used in the system can be various types, including regression models, neural networks, and deep learning models. Additionally, the patent covers a computer-implemented method and a non-transitory computer-readable medium storing instructions for implementing the method, emphasizing the importance of extracting clinically significant data from messages to optimize clinical workflows efficiently.

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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.