A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis

Personalised medicine and deep learning in interstitial lung disease and chronic obstructive pulmonary disease imaging

Chair(s): Adam Domonkos Tarnoki, Lucio Calandriello

Session type: Oral presentation

Simon Walsh

EVENTS HOME

Previous presentation

Next presentation

Session content

Late Breaking Abstract - Artificial intelligence-based decision support for HRCT stratification in fibrotic lung disease; an international study of 116 observers from 37 countries.

Lucio Calandriello

Replay

Poster

Abstract

Slides

Alveolar collapse as a prognostic marker in patients with IPF: A CT-based assessment using an extended parametric response mapping technique

Sarah Scharm

Replay

Poster

Abstract

Slides

In-vivo endobronchial-PS-OCT for fibrosis quantification in ILD

Tatiana Soldati

Replay

Poster

Abstract

Slides

Prognostic modeling in idiopathic pulmonary fibrosis using deep learning

Alexandre Coimbra

Replay

Poster

Abstract

Slides

A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis

Simon Walsh

Replay

Poster

Abstract

Slides

Deep learning-based quantification of traction bronchiectasis severity for predicting outcome in idiopathic pulmonary fibrosis

Federico Felder

Replay

Poster

Abstract

Slides

Comparison of parenchyma density scoring in RA-ILD vs IPF and iNSIP

Balint Acs

Replay

Abstract

Slides

Endobronchial polarization sensitive optical coherence tomography for airway wall imaging

Sofi Vassileva

Replay

Poster

Abstract

Slides

Towards precision medicine in COPD: Bioradiomic SPECT-CT quantification of active lung inflammation

Benjamin Welham

Replay

Poster

Abstract

Slides

Impaired xenon gas transfer observed two years after COVID-19 hospitalisation in patients with signs of interstitial lung disease

Helen Marshall

Replay

Poster

Abstract

Slides

Discussion and Q&A

The ERS International Congress 2023, Milan

#{title}