Seungwon Yang Leads Research Group Using AI to Detect Breast Cancer

October 18, 2022

BATON ROUGE - Seungwon Yang, PhD holds a joint position with the School of Information Studies (SIS) and the Center for Computation & Technology (CCT). During the past year, Yang collaborated with multiple universities to leverage artificial intelligence (AI) in the identification of breast cancer within mammogram images. Yang’s use of AI grew from discussions with colleagues at the Deep Learning Summit in Boston. As Yang discovered, breast cancer diagnosis from mammogram images remains shockingly low and inconsistent among radiologists. The low diagnosis rates frequently require patient reexamination with repeated radiation exposure and missed cancer cells.

Returning from the Deep Learning Summit, Yang assembled a team of doctoral students at CCT to focus on a deep learning algorithm that would find potentially cancerous regions and diagnose these regions for cancer cells. The group faced early challenges with data sharing between universities, but found success accessing an existing dataset of mammogram images from the University of South Florida, allowing them to continue their research.

The use of this AI deep learning algorithm for cancer detection is one of the first of its kind. It can automatically detect and diagnose areas based on a single mammogram image. If the newly developed algorithm is successful, a patient will be able to upload one image to the framework and the AI will detect suspicious regions of the mammogram and diagnose the region if something suspicious is found. While the initial results are promising, Yang and his research team are hoping to achieve higher performance as they gather more real-life mammogram data.

Through its initial development and testing, the AI algorithm performed very well, achieving a specificity of 93%, sensitivity of 94%, accuracy of 93.5%, precision of 93.39%, recall of 93%, and area under the curve (AUC) of 92.315%. An AUC of 100% would represent a perfect system, but an AUC in the range of 60-90% is considered good with anything over 90% demonstrating high performance. Yang and his team hope they will be able to assist with the advancement of accurate, reliable, and automated breast cancer diagnoses as their research move forward.

About SIS

The LSU School Information Studies (SIS) provides a 100% online prestigious education in library & information science. It is the home of the Master of Library & Information Science, which is the only program accredited by the American Library Association in the state of Louisiana. SIS also offers a dual degree with the Department of History, an undergraduate minor, and three graduate certificate options. SIS is a member of the iSchools, a group of Information Schools dedicated to advancing the information field. SIS is part of the LSU College of Human Sciences & Education.

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About CHSE

The College of Human Sciences & Education (CHSE) is a nationally accredited division of Louisiana State University. The college is comprised of the School of Education, the School of Information Studies, the School of Kinesiology the School of Leadership & Human Resource Development, the School of Social Work, and the University Laboratory School. These combined schools offer 8 undergraduate degree programs, 18 graduate programs, and 7 online graduate degree and/or certificate programs, enrolling more than 1,900 undergraduate and 1,120 graduate students. The College is committed to achieving the highest standards in teaching, research, and service and is committed to improving quality of life across the lifespan.

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