Salt Lake City, UT, United States of America

Diego Vargas

This inventor holds 1 USPTO granted patent. Top assignee: Myriad Genetics, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Diego Vargas. Retrieved from https://idiyas.com/inventor/diego-vargas

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Diego Vargas and AI-Driven Predictive Interactivity

Introduction

Diego Vargas is an inventor based in Salt Lake City, Utah. His patent work includes an artificial intelligence system designed to support patient interactions and inform healthcare recommendations.

Latest Patents

Vargas is associated with 1 patent, titled “Artificial Intelligence Predictive Interactivity Based on Recursive Data Analysis.” The invention describes an AI agent that interacts with patients through a computing device’s user interface. The agent can be trained using interaction logs and health-record data from a cohort of subjects. It may then use a patient’s interactions, along with information in that patient’s electronic health record, to recommend medical screenings or procedures. Data from additional patient interactions can also be used to update the models behind the agent.

Career Highlights

Vargas’s listed patent reflects an application of machine learning to patient engagement and personalized healthcare recommendations. He is associated with Myriad Genetics, Inc.

Collaborations

Among Vargas’s listed coworkers are Darshan Bhatt and Tanya Imani-Farley.

Conclusion

Diego Vargas’s patent describes an AI-based approach to combining patient interactions and health-record information to support personalized medical recommendations.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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