PathAI‘s patented method validates the performance of a trained model predicting tissue characteristics from pathology images. Users provide reference annotations for frames, processed by the model to generate predictions. Validation is based on the association between reference and predicted annotations. GlobalData’s report on PathAI gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on PathAI, AI-assisted medical imaging was a key innovation area identified from patents. PathAI's grant share as of February 2024 was 53%. Grant share is based on the ratio of number of grants to total number of patents.
Validating performance of a trained model for pathology images
A recently granted patent (Publication Number: US11915823B1) discloses a method for validating the performance of a trained model used to predict tissue and cellular characteristics from pathology images. The method involves receiving reference annotations from multiple users, processing the frames using the trained model to generate predicted annotations, and validating the model's performance by assessing the association between the reference and predicted annotations. The degree of association is determined by comparing user annotations within clusters and aggregating concordances to evaluate model performance.
Furthermore, the patent describes a system that implements the method, utilizing computer hardware processors and storage mediums to receive user annotations, process frames, generate model predictions, and validate the trained model's performance. The system evaluates the degree of association between reference and predicted annotations by comparing user annotations within clusters and aggregating concordances. The method and system aim to enhance the accuracy and reliability of predicting tissue and cellular characteristics from pathology images, offering a systematic approach to validate the performance of trained models in this domain.
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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
