Kuan Huang, an assistant professor and researcher at Kean University, is an expert on research involving new ways to detect breast cancer.
Huang, who teaches undergraduates and graduates, supervises student research and collaborates with other faculty to provide Kean students with research opportunities, has published more than 20 scientific papers on breast cancer detection and has appeared at international conferences.
Lately, however, he has been getting some additional help in his efforts.
Huang is researching the use of artificial intelligence in breast cancer screening, aiming to develop highly accurate diagnostic tools that can ultimately save lives.
“We want to develop an AI-based system that can be implemented in hospitals to assist in breast cancer diagnosis and treatment,” he said. “Our ultimate goal is to develop highly accurate AI that could eventually transform lives.”
Huang’s research utilizes real-patient ultrasound data from publicly available datasets. His team currently is analyzing approximately 2,000 images. The team, which includes six Kean student researchers, employs deep learning techniques, which use computer and math algorithms to help computers learn from real world examples.
“It mimics how humans learn through practice,” he said. “As a core part of AI, it enables computers to learn and make predictions automatically.”
A faculty member in the Department of Computer Science and Technology at the Dorothy and George Hennings College of Science, Mathematics and Technology, Huang’s work is at the intersection of computer science and health tech.
It’s a spot he’s been at for nearly a decade.
Huang’s research began when he was a graduate student at Utah State University in 2016.
“This work seeks to create a robust, accessible and publicly available AI framework that supports radiologists in identifying and classifying breast lesions more effectively.” — Kuan Huang
He continued his work during a postdoctoral fellowship at Baylor College of Medicine before bringing it to Kean in 2022.
Huang’s goal is to integrate AI tools into a comprehensive framework that could be used to guide doctors and radiologists in diagnosing breast cancer. He recently received a $203,000 National Science Foundation research grant to help him in his quest.
“This work seeks to create a robust, accessible and publicly available AI framework that supports radiologists in identifying and classifying breast lesions more effectively,” he said.
Patricia Morreale, a professor and chair of the department, said the university is blessed to have Huang’s research and expertise.
“The results of Dr. Kuan Huang’s work are highly impactful, both in the health care arena, as breast cancer tumors continue to have a high mortality rate, and in AI research, where his work in computer vision can be applied to similar problems,” she said.
Morreale said the research presents an incredible opportunity for students, too — further illustrating how Kean is becoming a top research university in the country.
“Working with Dr. Huang, students get exposure to the most advanced techniques for machine learning and have the experience of applying these methods to an important problem, cancer detection,” she said.
George Chang, dean of the college, said the potential impact of Huang’s research is huge.
“His work has the potential to greatly enhance the accuracy and efficiency of early detection, ultimately leading to better outcomes for patients,” Chang said. “The integration of AI into this vital screening process could reduce false positives and missed diagnoses, which are crucial for ensuring timely and appropriate treatment, while also empowering health professionals to better utilize AI technology in their practice.”
And while Huang will say that AI impact on health care will be huge — it may be able to detect details not visible to the human eye — he is equally quick to stress that AI alone is not enough.
“AI-assisted diagnostic tools cannot work alone,” he said. “Radiologists are still essential, with AI as a helpful assistant.”
For information about Kean University, go to kean.edu.
