Ho Yin Martin Yeung

Title: Ho Yin Martin Yeung: Innovator in Machine Learning for Disease Detection

Introduction

Ho Yin Martin Yeung is a prominent inventor based in Hong Kong, CN. He has made significant contributions to the field of machine learning, particularly in the area of disease detection. His innovative approach addresses the challenges associated with manual data annotation in medical imaging.

Latest Patents

Yeung holds a patent for a "Weakly-supervised system, method and workflow for processing whole slide image for disease detection." This invention provides a machine-learning model that detects carcinoma (CA) from whole slide images (WSI). By processing average cellular features of cells identified on the WSI, the model allows for the construction of training and testing datasets without the need for costly pixelwise labeling. The model not only predicts CA cases but also identifies suspicious cases for priority assessment and generates tumor probability heatmaps to assist in pathological evaluations.

Career Highlights

Throughout his career, Yeung has worked with esteemed institutions such as The Hong Kong Polytechnic University and The Chinese University of Hong Kong. His work has been instrumental in advancing the application of machine learning in healthcare.

Collaborations

Some of his notable coworkers include Ngai Nick Alex Wong and Jung Sun Yoo. Their collaborative efforts have contributed to the development of innovative solutions in the field of medical imaging.

Conclusion

Ho Yin Martin Yeung's contributions to machine learning and disease detection exemplify the impact of innovation in healthcare. His work continues to pave the way for advancements in medical technology and improved patient outcomes.