Presentation: Pathology
Kun-Hsing Yu, MD, PhD
Assistant Professor,
Harvard Medical School
What is your presentation about?
My presentation highlights the transformative role of artificial intelligence (AI) in cancer research and clinical diagnosis, with a particular focus on breast cancer. I will discuss recent advancements in AI-powered pathology foundation models and their effectiveness in analyzing high-resolution digital pathology images. In addition, I will address critical challenges in developing robust medical AI systems and propose research directions to overcome these hurdles, aiming to inspire innovative solutions that advance breast cancer care.
How do you hope your presentation will impact breast cancer research, care, or advocacy?
I hope my presentation will demonstrate how artificial intelligence can transform pathology diagnostic workflows for breast cancer patients. Additionally, I aim to highlight the urgent need to address challenges in AI development, ensuring these technologies are both robust and reliable for clinical applications.
How did you get involved in this particular area of breast cancer research, care, or advocacy?
My involvement in this field stems from a deep interest in using informatics to tackle critical challenges in cancer diagnosis and treatment. While developing AI applications in pathology, I recognized the transformative potential of machine learning for analyzing high-resolution digital images, particularly in breast cancer – a domain where accurate and timely diagnosis is essential for optimizing patient outcomes. My overarching goal has always been to bridge the gap between cutting-edge technology and meaningful clinical impact, fostering innovations that benefit patients and improve care.
Join us at SABCS 2025
Connect with thousands of basic and translational scientists, multidisciplinary clinicians, regulatory and pharmaceutical partners, survivors, and patient advocates at the 48th annual San Antonio Breast Cancer Symposium®. Complete your registration by Friday, September 26, to take advantage of discounted early registration rates.
