Hologic had eight patents in artificial intelligence during Q1 2024.Hologic Inc has developed systems and methods for predicting reading time and complexity of breast images by collecting data from various sources to train a predictive model. This model can estimate reading time and complexity for new breast images, helping prioritize mammographic studies and optimize radiologists’ time. GlobalData’s report on Hologic gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Hologic grant share with artificial intelligence as a theme is 37% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Ai system for predicting reading time and reading complexity for reviewing 2d/3d breast images (Patent ID: US20240021297A1)
The patent filed by Hologic Inc. describes systems and methods for predicting the reading time and complexity of breast images using a predictive model trained on data collected from various sources. The model analyzes image factors and training factors to estimate reading time and complexity, allowing for prioritization of mammographic studies and optimization of radiologists' time. The method involves assigning complexity labels based on expected reading time, correlations, and image data, and can adjust workload distribution based on these factors.
The system outlined in the patent includes a processor and memory with computer-executable instructions to receive mammographic exam data, provide it to a predictive model, and determine correlations between image factors and training factors to estimate reading time and assign complexity labels. The method further involves receiving a selection of the exam data and displaying the complexity label associated with the data. By utilizing this system, healthcare professionals can streamline the interpretation of breast images, prioritize readings, and optimize workflow based on the predicted reading time and complexity of the images.
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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.
