Portland, OR, United States of America

Eric Feczko

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Eric Feczko: Innovator in Heterogeneous Disorder Analysis

Introduction

Eric Feczko is a notable inventor based in Portland, Oregon. He has made significant contributions to the field of medical research, particularly in the analysis of heterogeneous disorders. His innovative approach utilizes advanced statistical models to improve the understanding and categorization of complex clinical conditions.

Latest Patents

Eric Feczko holds a patent titled "Subtyping heterogeneous disorders using functional random forest models." This patent outlines a method that includes identifying training data indicating features of a sample population and clinical outcomes associated with a heterogeneous condition. The method generates decision trees in a Random Forest (RF) based on the training data, which helps categorize the sample population into multiple categories. Additionally, a proximity matrix is created to indicate the proportion of decision trees that categorize individuals into the same categories. This innovative method aids in identifying subgroups of the heterogeneous condition by detecting communities within the proximity matrix.

Career Highlights

Eric Feczko is affiliated with Oregon Health & Science University, where he applies his expertise in statistical modeling and clinical research. His work has the potential to significantly impact the way heterogeneous disorders are understood and treated.

Collaborations

Some of his notable coworkers include Damien A Fair and Shannon K McWeeney, who contribute to the collaborative research environment at Oregon Health & Science University.

Conclusion

Eric Feczko's innovative work in the field of heterogeneous disorder analysis exemplifies the importance of advanced statistical methods in medical research. His contributions are paving the way for improved understanding and treatment of complex clinical conditions.

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