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AI Solution for Chest X-ray

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Proven accuracy leading to complete efficiency

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to try our AI?

Test yourself with our
INSIGHT Challenge!

97-99% AUC

Lunit INSIGHT CXR detects 10 abnormal radiologic findings with 97-99% accuracy.
(Tuberculosis screening on chest x-ray images is also supported.)

Nodule
Consolidation
Pneumothorax
Pleural effusion
Atelectasis
Pneumoperitoneum
Cardiomegaly
Mediastinal widening
Calcification
Fibrosis
Supports tuberculosis screening

Internal validation result : (version) v.3.1.5.0 / (date) Dec 21, 2022 / (dataset) 254K / (ROC AUC) 97~99% for 10 findings

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Global partnership

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Lunit INSIGHT CXR
user testimonial

Features

Optimized workflow

Reduce overall reading time via worklist prioritization with AI

Reading time for all cases and normal cases was reduced by 13% and 33%, respectively.¹

Read clinical evidence

1. Ju Gang Nam, Minchul Kim, et al. Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.

Read clinical evidence

1. Ju Gang Nam, Minchul Kim, et al. Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.

50% of lung cancer patients can be diagnosed earlier

Lunit INSIGHT CXR successfully analyzed the chest X-ray image of a 54-year-old male patient, detecting lung cancer 3 years prior to when it was diagnosed

  • 2013
  • 2014
  • 2015
  • 2016

Improved reading performance

Better detection of early-stage lung cancer without increasing false-positive cases.²

Read clinical evidence

1.Sowon Jang, Hwayoung Song, et al. Deep Learning–based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs.

Seamless integration

Regardless of your system, location, or environment, Lunit INSIGHT CXR will be seamlessly integrated into your existing workflow, transforming your reading experience.

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Publication

  1. Ju Gang Nam, Minchul Kim, et al. Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs. European Respiratory Journal. 2020
  2. Sowon Jang, Hwayoung Song, et al. Deep learning–based automatic detection algorithm for reducing overlooked lung cancers on chest radiographs. Radiology. 2020
Product manual download

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Publications featuring

The publications listed below are not subject to the review of medical device advertising and are intended to showcase Lunit’s technology.

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Learn more about Lunit INSIGHT CXR

What do the medical journals say about AI-powered chest x-ray?

Watch the animated video about Lunit INSIGHT CXR featured in peer-reviewed journals

Lunit INSIGHT MMG

Computer-Aided Detection / Diagnosis Software for Mammography

Publication

Making data-driven medicine a reality