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Detecting more breast cancers
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Rapid triage of normal cases
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Improving reading performance of general radiolog
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Supporting decision-making on BI-RADS 3 and
AI Solution for Mammography
Less doubts, More confidence
Lunit INSIGHT MMG is a cutting-edge AI solution designed to enhance breast cancer detection through mammography. With a proven 96% AUC accuracy, it helps radiologists detect malignant lesions, especially in dense breast tissues, improving diagnostic accuracy by up to 12%. Backed by studies published in The Lancet Digital Health and JAMA Oncology, and endorsed by global radiologists, Lunit INSIGHT MMG empowers earlier cancer detection, greater workflow efficiency, and more confident clinical decisions.
Normal / Benign mass
96% AUC Lunit INSIGHT MMG accurately detects lesions suspicious of breast cancer in a mammogram.
Malignant mass
96% AUC Lunit INSIGHT MMG accurately detects lesions suspicious of breast cancer in a mammogram.
Early Diagnosis of Breast Cancer
According to a study published in THE LANCET Digital Health in 2020, among the top 1% of Al scores for women with negative mammograms after double reading, Lunit Al found 12% interval cancers and 14% next round screen-detected cancers.
2022
2020
Enable early diagnosis of breast cancer
According to a study published in THE LANCET Digital Health Among the women with top AI scores for negative mammograms after double reading, 13% more cancers were detected earlier with Lunit INSIGHT MMG.²
Lunit's
Global Partners
40% of breast cancer patients can be diagnosed earlier
Lunit INSIGHT MMG successfully analyzed the mammogram of an overlooked case in 2020, where cancer was missed and the patient was diagnosed 2 years later in 2022.
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More interval cancers found
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More next round screen-detected cancers
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Dense breast cancer diagnosis increased by 9% with Al
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Fatty breast cancer diagnosis increased by 22% with Al
Improved Diagnostic Accuracy for Dense Breasts
Workflow efficiency
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According to a study published in THE LANCET Digital Health, Lunit INSIGHT MMG can triage 60% of the entire cases without missing any breast cancer.³ The suggested workflow model, of which the AI score functions as supportive information, reduces radiologists’ reading volume and complements their interpretations.
