Fractional Dynamics Foster Deep Learning of COPD Stage Prediction (Adv. Sci. 12/2023). Issue 12 (26th April 2023)

• Record Type: Journal Article
• Authors: Yin, Chenzhong; Udrescu, Mihai; Gupta, Gaurav; Cheng, Mingxi; Lihu, Andrei; Udrescu, Lucretia; Bogdan, Paul; Mannino, David M.; Mihaicuta, Stefan
• Is Part Of: Advanced science. Volume 10:Issue 12(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-04-26
• Subjects: Science -- Periodicals; 505
• DOI: 10.1002/advs.202370071
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract : Deep Learning Analyzing physiological signals with fractional dynamics reduces the learning complexity for automated diagnosis with deep learning. In article number 2203485, Mihai Udrescu, Paul Bogdan, and co‐workers show that fractional‐order dynamical modeling can extract distinguishing signatures from the physiological signals recorded in COPD patients, then use fractional signatures to develop and train a deep neural network that accurately predicts COPD stages—a robust alternative to spirometry.