egnite, Inc. Receives U.S. Patent for NLP-Based Algorithm That Classifies Mitral Regurgitation Mechanism from Echocardiographic Reports

PR Newswire
Today at 2:15pm UTC

egnite, Inc. Receives U.S. Patent for NLP-Based Algorithm That Classifies Mitral Regurgitation Mechanism from Echocardiographic Reports

PR Newswire

Patent recognizes egnite's novel approach to identifying degenerative, functional, and mixed MR at scale — enabling faster, more consistent clinical decision support

ALISO VIEJO, Calif., April 6, 2026 /PRNewswire-PRWeb/ -- egnite, Inc., a healthcare AI company focused on identifying and managing patients with untreated cardiovascular disease, today announced the issuance of U.S. Patent No. 12,580,057, titled "Systems and Methods for Natural Language Processing-Based Classification of Electronic Medical Records."

Patent recognizes egnite's novel approach to identifying degenerative, functional, and mixed MR at scale — enabling faster, more consistent clinical decision support

The patented technology addresses a longstanding clinical challenge: only 4% of echocardiographic reports clearly describe the likely etiology of mitral regurgitation. The remaining 96% are inconsistent, implicit, or non-standardized — leaving next steps unclear for providers and patients alike. egnite's algorithm reads echo report text and interprets clinician-documented findings to classify the most probable MR mechanism — primary degenerative, secondary functional, or mixed — enabling health systems to identify patients at scale and manage pathways systematically.

The algorithm applies a hierarchical, rules-based NLP framework informed by ACC/AHA guidelines and curated by cardiovascular specialists. Validated against a subset of egnite's 5.5 million deidentified echocardiographic reports, it achieved 97.3% accuracy in a maximal (population capture) configuration and 99.0% in a minimal (highest-confidence) configuration. The algorithm is now deployed live across over 600 healthcare facilities across the USA.

The clinical stakes are significant. Primary degenerative MR flags patients who may be candidates for surgical or transcatheter repair; secondary functional MR identifies patients for transcatheter edge-to-edge repair (TEER). For many of these patients, the window for intervention is narrow — and without the ability to interpret MR mechanism automatically across the entire at-risk patient population, health systems have no reliable way to find them in time.

"This patent reflects years of work at the intersection of cardiovascular medicine and applied AI," said Joel Portice, Chief Executive Officer of egnite. "Our goal has always been to help clinicians identify the right patients at the right time — not by replacing clinical judgment, but by making the insights already embedded in medical records actionable."

The patent names Kahla Verhoef and Dr. Michelle Kwon as inventors and is assigned to egnite, Inc.

About egnite, Inc.

egnite, Inc. is a rapidly growing data centric digital healthcare company that brings the power of artificial intelligence and technology to improving care for heart disease patients. egnite utilizes AI algorithms and big data to generate business intelligence for healthcare, elevating the role of data in critical decisions. The company, based in Aliso Viejo, California, partners with leading hospitals and life sciences organizations to transform care delivery for cardiovascular patients. For more information, visit www.egnitehealth.com.

egnite, egnite, Inc., CardioCare and the spark logo are trademarks of egnite, Inc.

Media Contact: Andro Yuson | andro.yuson@egnitehealth.com | 804-998-3066

Media Contact

Andro Yuson, egnite, 1 8049983066, andro.yuson@egnitehealth.com, https://egnitehealth.com/

Cision View original content:https://www.prweb.com/releases/egnite-inc-receives-us-patent-for-nlp-based-algorithm-that-classifies-mitral-regurgitation-mechanism-from-echocardiographic-reports-302733548.html

SOURCE egnite