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AI will be the new standard of care.By Lunit.

With AI,
we aim to make data-driven medicine
the new standard of care.
We are especially focused on
conquering cancer,
one of the leading causes
of death worldwide.

Happening now
at Lunit

All
Menu
News
Blog
Issue

  • Partnership News

    Lunit to Incorporate its Chest Detection Suite into Philips' Diagnostic X-ray Suite

  • COVID-19

    South Korean Medical AI Provider and PACS Leader Enters Indonesian Market, to Help COVID-19 Screening and Diagnosis

    Lunit Media • Jan 27, 2021
  • Chest

    Using AI to better manage COVID-19

    Minhong JangMinhong Jang • Jun 2, 2020

  • Products

    AI for Radiology and Oncology

    *Lunit lab at Samsung Medical Center, Seoul, Korea

  • Chest Radiology

    AI Proves Its Value in Assistance for Emergency Cases-- With Higher Accuracy and Timely Reporting Time of Chest Radiographs

    Lunit Media • Dec 24, 2020

  • Try Now

    Try using our AI online and see how our AI can help doctors

  • Evidence

    Making data-driven medicine a reality

  • Breast Radiology

    Recent Studies Reveal High Performance of Lunit AI in Breast Cancer Detection

    Lunit Media • Sep 10, 2020
  • COVID-19

    Lunit Releases Its AI Online to Support Healthcare Professionals Manage COVID-19

    Lunit Media • Mar 30, 2020
See more

Research and Publications

Lunit Evidence
All
Breast
Chest
Oncology
Breast

External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms

Mattie Salim, MD et al.

JAMA Oncology (2020)

Chest

Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study

Se Bum Jang et al.

PLOS ONE (2020)

Breast

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Thomas Schaffter, PhD et al.

JAMA Network Open (2020)

Breast

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study

Mattie Salim, MD et al.

Lancet Digital Health (2020)

Chest

Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs

Hyunsuk Yoo et al.

JAMA Network Open (2020)

Breast

Photometric Transformer Networks and Label Adjustment for Breast Density Prediction

Jaehwan Lee1 et al.

ICCV 2019 Workshop

Chest

SRM: A Style-based Recalibration Module for Convolutional Neural Networks

HyunJae Lee1 et al.

ICCV 2019

Chest

Learning Visual Context by Comparison

Minchul Kim et al.

ECCV 2020