Hod-HaSharon, Israel

Avishai Baruch Yaari

USPTO Granted Patents = 2 

 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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2 patents (USPTO):Explore Patents

Title: Avishai Baruch Yaari: Innovator in Machine Learning and Vascular Analysis

Introduction

Avishai Baruch Yaari is a notable inventor based in Hod-HaSharon, Israel. He has made significant contributions to the field of machine learning, particularly in the analysis of vascular features. With a total of two patents to his name, Yaari is recognized for his innovative approaches that combine modern technology with classical methods.

Latest Patents

Yaari's latest patents focus on systems and methods for machine-learning-based sensor analysis and vascular tree segmentation. These patents describe methods for the automated identification of vascular features. In some embodiments, one or more machine learning (ML)-based vascular classifiers are utilized, with their results being combined with those of at least one other vascular classifier to produce final results. The advantages of this approach include the ability to merge the strengths of ML classifiers with segmentation techniques based on more traditional, formula-based methods. This combination is particularly beneficial for identifying anatomically distinct targets that may appear similar within an image.

Career Highlights

Avishai Baruch Yaari is currently associated with Cathworks Ltd., where he continues to develop innovative solutions in the medical technology sector. His work is instrumental in advancing the capabilities of machine learning applications in healthcare.

Collaborations

Yaari collaborates with talented individuals such as Moran Shalhon Livne and Hila Blecher Segev, contributing to a dynamic and innovative work environment.

Conclusion

Avishai Baruch Yaari stands out as a pioneering inventor in the realm of machine learning and vascular analysis. His contributions are shaping the future of medical technology and enhancing the accuracy of vascular feature identification.

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