Summary of Deep Learning For Detecting and Early Predicting Chronic Obstructive Pulmonary Disease From Spirogram Time Series, by Shuhao Mei et al.
Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series
by Shuhao Mei, Xin Li, Yuxi Zhou, Jiahao Xu, Yong Zhang, Yuxuan Wan, Shan Cao, Qinghao Zhao, Shijia Geng, Junqing Xie, Shengyong Chen, Shenda Hong
First submitted to arxiv on: 6 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Deep learning-based approach, DeepSpiro, is introduced to predict future Chronic Obstructive Pulmonary Disease (COPD) risk by analyzing spirometry data. The model consists of four components: SpiroSmoother for stabilizing the volume-flow curve, SpiroEncoder for capturing volume variability patterns, SpiroExplainer for integrating heterogeneous data and explaining predictions, and SpiroPredictor for predicting COPD risk based on patch concavity. Evaluated on the UK Biobank dataset, DeepSpiro achieved an AUC of 0.8328 for COPD detection and demonstrated strong predictive performance for future COPD risk (p-value < 0.001). This deep learning-based approach has the potential to effectively predict the long-term progression of COPD disease. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way to predict when people might get a serious lung disease called Chronic Obstructive Pulmonary Disease (COPD) is developed. It uses special computer algorithms to look at breathing test results and find patterns that can help doctors predict who will develop COPD in the future. The new approach, called DeepSpiro, was tested on a large group of people and showed it could accurately predict when someone would develop COPD. |
Keywords
» Artificial intelligence » Auc » Deep learning
