Ka Fai To

Title: Innovations by Inventor Ka Fai To

Introduction

Ka Fai To is a notable 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 training machine learning models.

Latest Patents

Ka Fai To holds a patent for a "Weakly-supervised system, method and workflow for processing whole slide image for disease detection." This invention provides a solution for generating training and testing datasets without the need for costly pixelwise labeling of each cell on a whole slide image (WSI). The machine-learning model he developed is capable of detecting carcinoma (CA) by processing average cellular features of cells identified on the WSI. It 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, Ka Fai To has worked with prestigious institutions such as The Hong Kong Polytechnic University and The Chinese University of Hong Kong. His work has significantly advanced the capabilities of machine learning in medical diagnostics.

Collaborations

Ka Fai To has collaborated with notable colleagues, including Ho Yin Martin Yeung and Ngai Nick Alex Wong. Their combined expertise has contributed to the success of his innovative projects.

Conclusion

Ka Fai To'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 diagnostics.