Imaging biomarker development in fibrotic lung disease; applying deep learning to unsolved problems
Time: 8:30 am
day: Day One
Details:
- Reliable biomarkers allowing early disease detection, prediction of progression and measurement of therapeutic response are urgently needed in fibrotic lung diseases. Advances in deep learning technology have created new opportunities to identify, develop and validate new biomarkers by more precisely quantifying clinical and subclinical pulmonary disease.
- Specific imaging challenges to which deep learning may be applied include improved imaging diagnostics, classification of limited interstitial lung abnormalities based on disease behavior and prediction of the progressive pulmonary fibrosis using baseline imaging data.
- Qureight addresses these unmet clinical needs via imaging-based biomarker approaches. The presentation will focus on Qureight's deep learning models for classifying and quantifying disease severity in fibrotic lung disease, and their use in clinical trial and real-world patient imaging datasets
