Machine learning systems and methods for predicting risk of renal function decline

US10978176B2 · kind B2 · utility

Assignee

• pulseData Inc. · US

Inventors

• Theodore Cha · New York, US
• Hai Po Sun · New York, US
• Chris Kipers · New York, US
• Oliver Fielding · New York, US
• Jung Hoon Son · Palisades Park, US
• Edward Lee · Scarsdale, US

Key dates

• Filing date: Jul 1, 2019
• Grant date: Apr 13, 2021
• Expiry date: Jul 1, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H10/60
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Systems, methods and apparatuses are described herein that employ machine learning techniques to assess a likelihood or risk that one or more patients will experience an adverse outcome, such as a decline in renal function, within one or more timeframes. The embodiments may utilize patient data relating to demographics, vital signs, diagnoses, procedures, diagnostic tests, biomarker assays, genetic tests, behaviors, and/or patient symptoms, to determine risk information, such as important predictive features and patient risk scores. And the embodiments may automatically execute patient workflows, such as providing treatment recommendations to providers and/or patients, based on determined risk scores.