Siemens had 349 patents in artificial intelligence during Q2 2024. Siemens AG filed patents in Q2 2024 for methods and systems using artificial intelligence to predict radiation dosages during radiotherapy, interactive segmentation of volumetric imaging datasets using neural networks, calibrating digital twins of complex systems using sensor data and gradient optimization, generating motion-corrected MR image datasets, and generating synthetic cone-beam computed tomography information items for machine learning training. GlobalData’s report on Siemens gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Siemens had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Radiation dose prediction via artificial intelligence models using organ dose trade-off (Patent ID: US20240207644A1)
The patent filed by Siemens AG describes methods and systems for training and executing an artificial intelligence model to predict radiation dosages for different structures during radiotherapy treatment. The model is trained using a dataset of participants' dosages and organ structures, and it prioritizes between different organs at risk based on input values. The predicted dosages can be outputted, displayed in a dose-volume histogram, and transmitted to a plan optimizer software solution. Additionally, the system can adjust radiotherapy machine attributes based on the predicted dosages, and the model can be trained using weighted tensors and generative artificial intelligence models like variational auto-encoders.
The patent also covers a computer system and a system comprising a server, computer, and radiotherapy machine that work together to predict and output radiation dosages for organs at risk during treatment. The server receives prioritization values, executes the AI model, and outputs the predicted dosages. The system can display dose-volume histograms, receive multiple prioritization values, and adjust machine attributes accordingly. The AI model can be trained using weighted tensors and generative AI models. Overall, the patent aims to improve the accuracy and efficiency of predicting radiation dosages during radiotherapy treatment using artificial intelligence methodologies.
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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.
