Brainomix 360

Clinical Evidence

Explore peer-reviewed studies validating e-Lung’s performance and value, published by international academic groups. Brainomix products have been rigorously tested across diverse clinical settings—find the evidence here.

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The Brainomix automated e-ILD CT algorithm outperforms forced vital capacity in predicting outcomes for patients with idiopathic pulmonary fibrosis

September 7, 2022

Performance and Reproducibility of a Deep-learning Derived Automated Algorithm to Detect, Segment and Measure Lung Cancer Lesions on Computed Tomography Scans

January 1, 2023

In the Serial Assessment of Patients With Idiopathic Pulmonary Fibrosis, the Automated E-ILD CT Algorithm Outperforms Lung Function; a Validation Study

May 19, 2023

Novel e-Lung CT biomarkers combine to provide higher prognostic discrimination than FVC in patients with non-IPF fibrotic interstitial lung disease.

September 9, 2023

The automated e-Lung CT algorithm is more prognostic than lung function in patients with non IPF fibrotic ILD; a validation study

September 9, 2023

Clinical Evidence

Evaluation of Lung Volume Reduction in Patients with Interstitial Lung Disease Using Brainomix e-Lung (1)

Evaluation of Lung Volume Reduction in Patients with Interstitial Lung Disease Using Brainomix e-Lung

e-Lung CT biomarkers are associated with outcomes in fibrotic interstitial lung diseases

e-Lung computed tomography biomarkers are associated with outcomes in fibrotic interstitial lung diseases

Predictive Power of the e-Lung Weighted Reticulovascular Score for Mortality in Progressive Pulmonary Fibrosis

e-Lung Detects Progressive Pulmonary Fibrosis Earlier Than Conventional Tools: Insights from the REVISE-PPF Multicentre Study

Phase 2 study design and analysis approach for BBT-877: an autotaxin inhibitor targeting idiopathic pulmonary fibrosis

Baseline quantitative CT predicts rate of decline in forced vital capacity and clinically relevant outcomes in patients with progressive pulmonary fibrosis: results from the INBUILD trial

Effect of Nintedanib on Quantitative CT in Patients With Progressive Pulmonary Fibrosis: Results From the Inbuild Trial

e-Lung Biomarkers Are Associated with Future Progressive Pulmonary Fibrosis Independent of UIP Status on CT

A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease

Evaluation of e-Lung automated quantitative computed tomography biomarkers in idiopathic pulmonary fibrosis

e-Lung CT Biomarkers Can Stratify Patients at Risk of IPF Progression at 52 Weeks; Post-hoc Analysis From a Randomised Control Trial

e-Lung Computed Tomography Biomarker Stratifies Patients at Risk of Idiopathic Pulmonary Fibrosis Progression in a 52-Week Clinical Trial

Novel e-Lung CT biomarkers combine to provide higher prognostic discrimination than FVC in patients with non-IPF fibrotic interstitial lung disease.

The automated e-Lung CT algorithm is more prognostic than lung function in patients with non IPF fibrotic ILD; a validation study

In the Serial Assessment of Patients With Idiopathic Pulmonary Fibrosis, the Automated E-ILD CT Algorithm Outperforms Lung Function; a Validation Study

Performance and Reproducibility of a Deep-learning Derived Automated Algorithm to Detect, Segment and Measure Lung Cancer Lesions on Computed Tomography Scans

The Brainomix automated e-ILD CT algorithm outperforms forced vital capacity in predicting outcomes for patients with idiopathic pulmonary fibrosis