Bethesda, MD, United States of America

Yifan Peng

USPTO Granted Patents = 1 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Yifan Peng: Innovator in Medical Imaging Technology

Introduction

Yifan Peng is a prominent inventor based in Bethesda, MD (US). He has made significant contributions to the field of medical imaging, particularly in the development of advanced databases for chest X-ray analysis. His work focuses on improving the detection and classification of thoracic diseases through innovative methodologies.

Latest Patents

Yifan Peng holds a patent titled "Method and system of building hospital-scale chest X-ray database for entity extraction and weakly-supervised classification and localization of common thorax diseases." This patent introduces a new chest X-ray database, known as 'ChestX-ray8', which contains over 100,000 frontal view X-ray images from more than 32,000 unique patients. The database is enhanced with text-mined labels for eight common diseases, allowing for multi-label classification. The framework developed by Peng enables the detection and spatial localization of these diseases using a weakly supervised multi-label image classification approach, validated through the disclosed dataset.

Career Highlights

Yifan Peng is associated with the United States of America, as represented by the Secretary, Department of Health and Human Services. His work has been instrumental in advancing the capabilities of medical imaging technologies, particularly in the context of chest X-rays.

Collaborations

Yifan has collaborated with notable colleagues, including Xiaosong Wang and Le Lu, who have contributed to the research and development of the chest X-ray database and its applications.

Conclusion

Yifan Peng's innovative work in medical imaging technology, particularly through his patent on the ChestX-ray8 database, showcases his commitment to enhancing healthcare diagnostics. His contributions are paving the way for improved detection and classification of thoracic diseases, ultimately benefiting patient care.

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