Medical AI company Lunit announced that it will present 14 research abstracts related to its AI medical image analysis solutions at the 2025 Radiological Society of North America (RSNA 2025), to be held in Chicago from November 30 to December 4. Eight of these abstracts were accepted for oral presentations, which are considered key research achievements at the conference.
The oral presentations include: ▲Comparison of DBT interpretation and breast cancer detection performance of commercial AI algorithms using Dutch breast cancer screening data; ▲Comparison of screening performance based on mammography; ▲The impact of AI on decision-making and viewing behavior of radiologists; ▲Changes in breast cancer screening paradigm based on AI-integrated interpretation; ▲Comparison of the accuracy of detecting pneumothorax in chest X-ray.
Research related to breast density and breast cancer risk analysis will also be presented. Oral presentations will cover topics such as: ▲A comparison of high-risk group estimates using breast density with existing risk prediction models; ▲The impact of breast density changes on the accuracy of risk prediction models; and ▲An analysis of the correlation between breast density and pathologic prognosis stage in the UK Breast Cancer Screening Program.
Poster presentations include: ▲Optimization of early detection of contralateral breast cancer after breast cancer surgery; ▲Analysis of breast cancer subtypes that are easily missed in DBT; ▲Comparison of breast cancer prediction performance and synergy analysis; ▲Prediction of estrogen receptor-positive breast cancer risk score; ▲Prediction of lymph node metastasis and complete remission after neoadjuvant chemotherapy.
Seo Beom-seok, CEO of Lunit, said, “At RSNA 2025, we will present research results in areas of AI technology application, such as breast cancer screening, risk prediction, and lung disease diagnosis,” and added, “We expect there to be a lot of interest from academia and industry, as it includes studies that demonstrate the influence of AI in actual medical settings, and we will strive to translate this into business results.”
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