Lunit INSIGHT CXR

Lunit INSIGHT CXR

Lunit INSIGHT CXR

Country of origin

šŸ‡°šŸ‡·

Subspecialities

Chest

Modality

XR

Disease targeted

Population

Patients aged 14 years or older

Certification

Certified, Class I , MDD

On market since

November 1, 2019

ClinicalĀ information

Lunit INSIGHT CXR is deep learning based software that assists radiologists or clinicians in the interpretation of chest x-ray (PA/AP). The AI solution automatically detects 10 radiologic findings including atelectasis, calcification, cardiomegaly, consolidation, fibrosis, mediastinal widening, nodule, pleural effusion, pneumoperitoneum, and pneumothorax. The analysis result contains (1) localization of suspicious areas in color or outline, (2) abnormality scores reflecting the probability that the detected lesion is abnormal, and (3) text interpretation for the analysis result by each finding.

DiseaseĀ targeted

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Sample images

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Videos

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Sample studies

Scientific

The impact of artificial intelligence on the reading times of radiologists for chest radiographs

Author

Journal

Nature

Publication

Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs

Author

Journal

Publication

AI Improves Nodule Detection on Chest Radiographs in a Health Screening Population : A Randomized Controlled Trial

Author

Journal

Publication

Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease prevalence

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Publication

Validation study of machine-learning chest radiograph software in primary and emergency medicine

Author

Journal

Publication

Association of Artificial Intelligenceā€“Aided Chest Radiograph Interpretation With Reader Performance and Efficiency

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Journal

Publication

Successful Implementation of an Artificial Intelligence-Based Computer-Aided Detection System for Chest Radiography in Daily Clinical Practice

Author

Journal

Publication

Diagnostic performance of artifcial intelligence approved for adults for the interpretation of pediatric chest radiographs

Author

Journal

Nature

Publication

Deep Learning for Detecting Pneumothorax on Chest Radiographs after Needle Biopsy: Clinical Implementation

Author

Journal

Publication

Effect of deep learning-based assistive technology use on chest radiograph interpretation by emergency department physicians: a prospective interventional simulation-based study

Author

Journal

Publication

Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms

Author

Journal

The Lancet

Publication

Development and Validation of Deep Learningā€“based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs

Author

Journal

Publication

Development and Validation of a Deep Learningā€“based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs

Author

Journal

Publication

Development and Validation of a Deep Learningā€“Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs

Author

Journal

Publication

Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems

Author

Journal

Nature

Publication

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department

Author

Journal

Publication

Test-retest reproducibility of a deep learningā€“based automatic detection algorithm for the chest radiograph

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Journal

Publication

Technical information

Input

chest PA(posterior-anterior view), chest AP(anterior-posterior view)

Integration types

This product does not have Integration types

Trigger

Automatically, right after the image acquisition

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