New research demonstrates that Lunit INSIGHT MMG, an AI-based mammography analysis tool, can reduce radiologists' workload by approximately 70% by streamlining the categorization of mammograms.

The AI does this by sorting scans into groups that require immediate review, further evaluation, or no action, based on AI-generated risk assessments. Moreover, the study recorded a 30.5% increase in cancer detection accuracy.

The study, published in the journal European Radiology , was conducted across several universities in Turkey including Acibadem Mehmet Ali Aydinlar University and Istanbul University, and examined data from over 22,621 mammograms across a decade.

One of the critical findings from the study was the AI system's ability to identify 51.72% of interval cancers and 50% of cancers that were initially missed. Additionally, employing the AI as a second reader could potentially hasten diagnosis by nearly 30 months, compared to traditional methods.

Brandon Suh, CEO of Lunit, emphasized the dual benefits of integrating AI in medical diagnostics. "This research showcases not only the medical efficacy of Lunit INSIGHT MMG but also its potential to enhance operational efficiency and economic value within healthcare systems," he stated.

Founded in 2013, Lunit has focused on the development of deep learning-based medical AI technologies to aid in cancer diagnosis and treatment. The company's advancements have been recognized in numerous peer-reviewed journals and global conferences. Following FDA clearance and receiving the CE Mark, the Lunit INSIGHT suite is now used clinically in over 3,000 hospitals and medical institutions across more than 40 countries.

As AI continues to permeate various facets of healthcare, studies like this underscore its potential to not only improve medical outcomes but also streamline healthcare operations, making high-quality care more accessible and efficient.

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