Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/36867
Title: Modelling the impact of the disease on people with COPD: a comparison of feature selection methods
Author: Cabral, Jorge
Macedo, Pedro
Marques, Alda
Afreixo, Vera
Keywords: COPD
COVID-19
Feature selection
Normalized entropy
Lasso
Stepwise selection
Issue Date: 2022
Publisher: JSHD
Abstract: Lockdown due to The COVID-19 pandemic is likely to have influenced the daily life of people with chronic obstructive pulmonary disease. Criteria to choose the most appropriate methods to select features in datasets are unclear. We aimed to compare feature selection methods and describe the effect of the COVID-19 lockdown, sociodemographic and clinical features on the impact of the disease on people with COPD. A total of 42 participants with mean age 66.3 years (sd 7.8), 3 to 4 comorbidities (64.3%) and a median CAT score of 9.0 ([Q1,Q3]=[5.3,11.0]) were included, 24 (57.1%) of whom in the pre-lockdown group. The model obtained with 3 features selected by the entropy approach was at least not worse than the remaining. Our model suggests that lockdown had no influence in COPD impact but those with comorbidities but no emergencies tended to recover well from the pandemic.
Peer review: yes
URI: http://hdl.handle.net/10773/36867
DOI: 10.34624/jshd.v4i1.29107
ISSN: 2184-5794
Appears in Collections:Lab3R - Comunicações

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