Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata

Mohamed Dahmane

2024

Abstract

Pulmonary Fibrosis (PF) is a progressive chronic illness in which the lung tissues become increasingly scarred and damaged, leading to irreversible loss of their capacity to oxygenate vital organs. The specific causes of the illness are often unknown in many cases. Assessment of the severity of the lung disease is critical for physicians to diagnose PF early, control disease decline, and manage damage progression. The Forced Vital Capacity (FVC) of the lungs measured by a spirometer, is a good indicator of the severity of the condition of the lungs. In this work, we investigated an approach for early diagnosis of PF and showcased a multimodal architecture that predicts the FVC of patients at different stages of the disease. We propose an anti-Elu intermediate block and an anti-Relu confidence block to predict the pulmonary fibrosis progression. The uncertainty estimation block proved effective in predicting the FVC using data from initial spirometry measurements, clinical meta-data and CT images. Evaluation of the model on the OSIC pulmonary fibrosis progression dataset showed improved performance compared to state-of-the-art methods, with an average modified Laplace log-likelihood score of -6.8227 on a private test set.

Paper Citation

in Harvard Style

Dahmane M. (2024). Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 461-468. DOI: 10.5220/0012304100003660

in Bibtex Style

@conference{visapp24,
author={Mohamed Dahmane},
title={Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={461-468},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012304100003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata
SN - 978-989-758-679-8
AU - Dahmane M.
PY - 2024
SP - 461
EP - 468
DO - 10.5220/0012304100003660
PB - SciTePress