Bayer had 35 patents in artificial intelligence during Q2 2024. Bayer AG filed patents in Q2 2024 for methods and systems involving machine learning models to establish links between different types of medical data, processing medical images using clinical applications, training prediction tools to generate synthetic images, training neural networks for image processing, and controlling application of agrichemical products based on remotely sensed digital image data. GlobalData’s report on Bayer gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Bayer had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Method and apparatus for processing of multi-modal data (Patent ID: US20240212811A1)
The patent filed by Bayer AG describes a method for training a machine learning model that can establish connections between different types of data by creating a joint representation, specifically focusing on medical data such as electronic medical records and medical images. The trained model can perform tasks like autocompleting incomplete data, detecting uncertain or spurious data, and generating probable data. The method involves obtaining input and test text and image data, generating a joint representation, evaluating the model's performance based on loss functions, and adjusting parameters to reduce deviations between output and desired data.
The method includes steps for handling edited and unedited source data, cropping and corrupting text and image data, and changing parameters based on deviation thresholds. It also involves encoding text and image data, combining them into a joint representation, and decoding to generate output data. The patent further details the use of artificial neural networks, backpropagation for parameter changes, and the inclusion of patient information in the input data. Additionally, the patent discusses the comparison of different representations, the use of an apparatus with processors and memory for data processing, and the generation of new output data based on new input data using the trained machine learning model.
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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.
