Multi-Modal Multi-Task Foundational Models for Medical Image Manipulation
Summary
The USPTO published patent application US20260094693A1 on April 2, 2026, disclosing a multi-modal AI system developed by inventors Alexandru Constantin Serban, Mehmet Akif Gulsun, Puneet Sharma, and Dorin Comaniciu for medical image manipulation and information retrieval. The system receives text-based instructions, encodes them using machine learning text encoders, and determines and performs instructions through medical applications to generate responses. The publication affects medical device makers, healthcare technology providers, and AI developers working on clinical applications.
What changed
The USPTO published patent application US20260094693A1 disclosing systems and methods for multi-modal multi-task foundational models that process text-based instructions to perform actions on medical applications. The technology uses machine learning text encoder networks to convert text instructions into features, a policy module to determine executable instructions, and medical applications to perform those instructions and generate responses for medical image manipulation and information retrieval.
No immediate compliance action is required as this is a patent publication rather than a regulatory requirement. However, medical device manufacturers, healthcare technology companies, and AI developers should review the patent claims to assess potential IP landscape implications for their own medical AI products. Companies developing similar text-instructed medical imaging systems may need to evaluate freedom-to-operate considerations.
Archived snapshot
Apr 2, 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.
MULTI-MODAL MULTI-TASK FOUNDATIONAL MODELS FOR MEDICAL IMAGE MANIPULATION AND INFORMATION RETRIEVAL
Application US20260094693A1 Kind: A1 Apr 02, 2026
Inventors
Alexandru Constantin Serban, Mehmet Akif Gulsun, Puneet Sharma, Dorin Comaniciu
Abstract
Systems and methods for automatically performing one or more actions on one or more medical applications are provided. Text-based instructions are received. The text-based instructions are encoded into text features using a machine learning based text encoder network. One or more instructions for performing by one or more medical applications are determined using a policy module based on the text features. The one or more instructions are performed by the one or more medical applications to generate a response to the text-based instructions. The response to the text-based instructions is output.
CPC Classifications
G16H 30/40 G06F 40/279 G06V 10/7715 G06V 10/82 G06V 10/945 G06V 2201/03 G10L 15/22 G10L 2015/223
Filing Date
2024-09-27
Application No.
18898763
Named provisions
Related changes
Get daily alerts for USPTO Patent Applications - 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 Applications - Health Informatics (G16H) publishes new changes.
Subscribed!
Optional. Filters your digest to exactly the updates that matter to you.