Paige.AI had one patents in internet of things during Q4 2023. Paige.AI Inc’s patent filed in Q4 2023 describes systems and methods for processing electronic medical images to predict histological morphologies based on pathology specimens and patient clinical data using a trained machine learning system. The prediction is then output to a user or storage. 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 internet of things 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: Systems and methods to process electronic images for histological morphology trajectory prediction (Patent ID: US20230386031A1)
The patent filed by Paige.AI Inc. describes systems and methods for processing electronic medical images to predict histological morphologies based on pathology specimens associated with a patient. The method involves receiving digital medical images and patient clinical data, determining a trained machine learning system, providing the data to the system, determining a histological morphology prediction, and outputting the prediction to a user or storage. The system can also incorporate patient environmental data, location data, and risk settings to enhance the accuracy of the predictions. Additionally, the method includes identifying salient image regions, determining confidence levels in the predictions, and generating alerts for healthcare professionals or patients based on the predicted histological morphology trajectories.
The system described in the patent includes a memory storing instructions and a processor to execute the operations involved in predicting histological morphologies from medical images and patient data. The system can receive various types of patient data, including clinical, environmental, and location data, to improve the accuracy of the predictions. It also includes features such as identifying salient image regions, incorporating risk settings, determining confidence levels, and generating alerts for follow-up appointments or procedures based on the predicted histological morphology trajectories. Overall, the system and method outlined in the patent aim to leverage machine learning techniques to predict histological morphologies from electronic medical images, providing valuable insights for healthcare professionals and patients.
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