PathAI Patent - AI Pathology Tissue Prediction Statistical Model
Summary
The USPTO granted Patent US12597523B1 to PathAI, Inc. on April 7, 2026. The patent covers systems and methods for training a statistical model to predict tissue characteristics for pathology images using annotated image patches and machine learning techniques. The patent contains 17 claims and was filed on January 16, 2024.
What changed
The USPTO issued Patent US12597523B1 to PathAI, Inc. for an AI-based method of training statistical models to predict tissue characteristics from pathology images. The invention involves accessing annotated pathology images, defining training patches with corresponding annotations, and training a statistical model based on these patches. The patent is classified under CPC codes G16H 10/20 (Healthcare informatics), G06F 16/5866 (Image retrieval), and G06N 5/046 (Knowledge-based systems).
For PathAI and competitors in digital pathology and AI-driven medical diagnostics, this patent establishes intellectual property rights that may affect freedom-to-operate considerations. Healthcare providers and medical device manufacturers implementing AI-based pathology analysis solutions should evaluate potential licensing requirements or design-around strategies to avoid infringement claims.
What to do next
- Monitor for post-grant review opportunities
- Review patent claims for freedom-to-operate analysis
- Assess potential licensing or enforcement implications
Archived snapshot
Apr 7, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Systems and methods for training a statistical model to predict tissue characteristics for a pathology image
Grant US12597523B1 Kind: B1 Apr 07, 2026
Assignee
PathAI, Inc.
Inventors
Andrew H. Beck, Aditya Khosla
Abstract
In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.
CPC Classifications
G16H 10/20 G06F 16/5866 G06N 5/046
Filing Date
2024-01-16
Application No.
18413359
Claims
17
Related changes
Get daily alerts for USPTO Patent Grants - Health Informatics (G16H)
Daily digest delivered to your inbox.
Free. Unsubscribe anytime.
Source
About this page
Every important government, regulator, and court update from around the world. One place. Real-time. Free. Our mission
Source document text, dates, docket IDs, and authority are extracted directly from USPTO.
The summary, classification, recommended actions, deadlines, and penalty information are AI-generated from the original text and may contain errors. Always verify against the source document.
Classification
Who this affects
Taxonomy
Browse Categories
Get alerts for this source
We'll email you when USPTO Patent Grants - Health Informatics (G16H) publishes new changes.
Subscribed!
Optional. Filters your digest to exactly the updates that matter to you.