Comparison of the Baseline Clinical and HRCT Characteristics of Insilico’s ISM001_055 Phase 2a Trial Cohort in China with Real-World IPF Datasets
2025 ERS Abstract
PMG1015 Demonstrates a Well-Tolerated Safety Profile and Favorable FVC Changes after 12 Weeks of Treatment in IPF Patients
2025 ERS Abstract
Deep Learning-based Fibrosis and Ground Glass Opacification Quantification with Proteomic Biomarkers for Outcome Prediction in Idiopathic Pulmonary Fibrosis.
2025 ERS Abstract
Longitudinal Changes in Quantitative Imaging Biomarkers are Associated with Increased Risk of Mortality in Connective Tissue Disease-Related Interstitial Lung Disease
2025 ERS Abstract
Deep Learning-Based Airway and Vessel Volume are Associated with Increased Risk of Mortality in Connective Tissue Disease-Related Interstitial Lung Disease.
2025 ERS Abstract
Deep Learning-based Image Quantification of CTPA to Phenotype Pulmonary Arterial Hypertension
2025 ERS Abstract
Deep Learning Analysis of Serial CT Scans Correlates with Changes in how Patients Feel, Function and Survive in Fibrotic Interstitial Lung Disease
2025 ERS Abstract
The Role of Quantitative CT in the Prognostication and Monitoring of Systemic Autoimmune Rheumatic Disease Related Interstitial Lung Disease
2025 BTS Abstract
Pulmonary Blood Volumes on CT Predict Residual Pulmonary Hypertension Post-Pulmonary Endarterectomy
Combined Deep Learning Algorithms Demonstrate That Both Computed Tomography Phenotype and Anatomical Biomarkers Are Predictive of Prognosis and Progression in Idiopathic Pulmonary Fibrosis
ATS Journals
The Potential for Deep Learning Technology in Clinical Trials
Journal of Clinical Studies
Deep Learning Quantitative Computed Tomography Analysis in the Australian Idiopathic Pulmonary Fibrosis Registry
ATS Journals
Deep Learning-based Disease Severity Biomarkers on CT; Posthoc Analysis in a Phase 2a Placebo-controlled Study of ENV-101 in Subjects With Idiopathic Pulmonary Fibrosis
ATS Journals
Monte Carlo External Control Arm Generation Utilising Real-world Patient Data and Deep Learning-based Quantitative CT Metrics Demonstrates Treatment Effect in the Atlas IPF Trial
ATS Journals
Deep Learning-Based Short-Term Disease Progression Evaluation Supersedes Automated Baseline CT Phenotype in Predicting Outcomes in Idiopathic Pulmonary Fibrosis
ATS Journals
Deep Learning-Based Quantitative CT and CT Phenotype Classification Independently Predict Mortality in Idiopathic Pulmonary Fibrosis, a Prospective Observational Cohort Study
ATS Journals
Deep Learning-based Quantitative CT and Proteomics for Predicting Outcomes in Idiopathic Pulmonary Fibrosis
ATS Journals
Dose-Dependent Change of Inhaled Pirfenidone Seen in Lung Volume and Fibrosis Quantification in Patients With IPF: A Deep Learning Image-Based Analysis of Data From the ATLAS Phase 1b Trial
ATS Journals