At RSNA 2023, Lunit will display seven AI studies aimed at enhancing diagnostic efficiency in chest radiography and breast cancer risk evaluation. The presentations will showcase advancements like AI algorithms that improve the accuracy of chest x-ray reporting and the predictive analysis of breast cancer risks from mammography data. Lunit’s technology aids radiologists and has been adopted by over 2000 medical institutions globally, reflecting its influence on international health challenges.
Lunit, an innovator in AI-driven cancer diagnostic and treatment solutions, is poised to introduce seven groundbreaking studies at the forthcoming RSNA 2023, an influential annual event organized by the Radiological Society of North America. The meeting, which will host radiological experts from around the globe, is scheduled for November 26-30 in Chicago. Lunit’s presence underscores its commitment to advancing the field of radiology through artificial intelligence, with two oral presentations and a suite of five electronic posters (ePosters) lined up.
The RSNA conference, known for showcasing cutting-edge medical imaging research and technology, will feature Lunit’s presentations focusing on key areas: the improvement of reporting efficiency for chest radiographs and the enhancement of breast cancer risk assessment methods. Lunit will highlight how its AI model streamlines chest X-ray analyses by effectively differentiating between normal and abnormal scans. This not only lightens the radiologists’ burden but also serves as a critical backup to ensure diagnostic accuracy.
One of Lunit’s oral presentations will reveal the integration of novel and pre-existing AI algorithms to expedite the reading of chest x-rays. This presentation will show how AI can potentially transform routine radiographic assessments, making them more efficient and less taxing for radiologists.
In a joint study with Swedish researchers, Lunit will also present the performance evaluation of its Lunit INSIGHT MMG tool. This second oral presentation is aimed at demonstrating the AI’s effectiveness in comparison to human radiologists by presenting data on accuracy and reliability.
The set of ePosters that Lunit is bringing to RSNA encompasses a range of explorations into AI’s role in cancer screening and diagnosis. One poster will introduce an innovative AI model that scrutinizes mammographic patterns and changes over time, offering predictions on breast cancer risk that go beyond traditional mammographic density measures.
Another ePoster presents a comparative analysis focusing on the diagnostic accuracy of radiologists using Lunit’s AI-enhanced breast cancer screening tool versus traditional methods. Lunit’s investigation into the adjunctive use of breast ultrasound in conjunction with their AI technology in mammography, particularly for women with dense breast tissue, is also a part of their ePoster presentations. Moreover, Lunit will delve into the specifics of mammogram false negatives produced by its computer-aided detection and diagnosis systems, paying close attention to invasive breast cancers and their molecular subtypes.
Lunit’s CEO, Brandon Suh, emphasizes the company’s regular participation in the RSNA meetings and consistent revelation of innovative research since 2016. Lunit’s dedication to refining its AI offerings is integral to its mission of revolutionizing cancer screening, particularly for chest and breast cancer.
In addition to their scientific contributions, Lunit will enhance the RSNA experience by hosting an interactive exhibit at booth #4165 within the AI Showcase section. This platform will allow attendees to engage directly with Lunit’s technologies. The company boasts a global impact, with its AI solutions deployed in over 2000 healthcare institutions, tackling significant health challenges worldwide.
This year’s RSNA is set to be a pivotal stage for Lunit, allowing the company to share its scientific advancements and reinforce its position as a leader in the AI healthcare space. The company’s breakthroughs represent a significant stride forward in using AI to augment the efficacy and accuracy of cancer diagnostics, which in turn has the potential to improve patient outcomes across the world.
