Mountain View, CA, United States of America

Chace Lee


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations in Maternal Health Diagnostics by Chace Lee

Introduction

Chace Lee is an innovative inventor based in Mountain View, CA (US). He has made significant contributions to the field of maternal and prenatal health diagnostics. His work focuses on utilizing advanced machine learning techniques to enhance the accuracy and efficiency of ultrasound diagnostics.

Latest Patents

Chace Lee holds a patent for an invention titled "Automated maternal and prenatal health diagnostics from ultrasound blind sweep video sequences." This system generates diagnostic information from video sequences of ultrasound images acquired in 'blind sweeps,' meaning the operator does not see the images as they are captured. The patent describes two distinct machine learning systems for predicting diagnostic information: a “Temporal Accumulation” system and a “3-D Modeling Component” system. These systems can be implemented individually or in combination, providing flexibility in their application. Additionally, the invention includes a computing system that features an image selection system, which utilizes machine learning models to identify clinically suitable images, and an image diagnosis/measurement system that processes these images to predict health states.

Career Highlights

Chace Lee is currently employed at Google Inc., where he continues to develop innovative solutions in health technology. His work is pivotal in advancing the capabilities of ultrasound diagnostics, making significant strides in maternal health.

Collaborations

Chace collaborates with talented individuals such as Ryan Gomes and Shravya Shetty, contributing to a dynamic team focused on pushing the boundaries of health technology.

Conclusion

Chace Lee's contributions to automated maternal and prenatal health diagnostics exemplify the intersection of technology and healthcare. His innovative patent showcases the potential of machine learning in improving diagnostic processes, ultimately benefiting maternal health outcomes.

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