Paige.AI had 23 patents in artificial intelligence during Q4 2023. Paige.AI Inc’s patents in Q4 2023 focus on systems and methods for verifying slide and block quality for testing, using an integrated computing platform for digital pathology slides with AI, processing images to determine quality control metrics, predicting donor recipients for transplant patients, and predicting histological morphologies from electronic medical images. These innovations leverage machine learning models to improve the accuracy and efficiency of pathology and medical image analysis. GlobalData’s report on Paige.AI gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Paige.AI grant share with artificial intelligence as a theme is 21% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Systems and methods for artificial intelligence powered molecular workflow verifying slide and block quality for testing (Patent ID: US20230420116A1)
The patent filed by Paige.AI Inc. discloses systems and methods for verifying the quality of slides and blocks used for testing in the medical field. The method involves applying a machine learning model to digital images associated with tissue blocks to identify specific attributes, determining the amount or percentage of tissue with the attribute, and outputting a quality score based on this determination. The quality score is calculated based on whether the amount or percentage of tissue with the attribute is below a predetermined value, with different scoring mechanisms in place for different scenarios.
Additionally, the method includes partitioning digital images into tiles, detecting and segmenting tissue regions, and removing background tiles to enhance accuracy. The system described in the patent utilizes machine learning models to determine tissue quality and output corresponding quality scores. The method also involves providing feedback to users based on the quality scores, such as indicating the need for additional slides or preparing new tissue blocks for testing. Overall, the patent focuses on leveraging machine learning and image analysis techniques to assess the quality of tissue samples for medical testing, with a particular emphasis on optimizing the testing process based on the quality scores obtained.
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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.
