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

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

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

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

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

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

Photometric Transformer Networks and Label Adjustment for Breast Density Prediction

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

Learning Visual Context by Comparison

Reducing Domain Gap by Reducing Style Bias

Deep learning from HE slides predicts the clinical benefit from adjuvant chemotherapy in hormone receptor-positive breast cancer patients

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset

Application of artificial intelligence–based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms

Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort

Undetected Lung Cancer at Posteroanterior Chest Radiography: Potential Role of a Deep Learning–based Detection Algorithm

Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs

Performance of a Deep-learning Algorithm Compared to Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population

Deep-learning Based Automated Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs: Diagnostic Performance in Systematic Screening of Asymptomatic Individuals

Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration

Deep Learning–based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs

Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses

Clinical Validation of a Deep Learning Algorithm for Detection of Pneumonia on Chest Radiographs in Emergency Department Patients with Acute Febrile Respiratory Illness

Implementation of a Deep Learning-Based Computer-Aided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study

Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

Test-retest reproducibility of a deep learning–based automatic detection algorithm for the chest radiograph

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department

Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge

Development and Validation of a Deep Learning–based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs

Development and Validation of a Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs

Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study