Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers-Reference-Cited by-同舟云学术

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Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers

Published:2021-05-01 Issue:5 Volume:42 Page:054001
ISSN:0967-3334
Container-title:Physiological Measurement
language:
Short-container-title:Physiol. Meas.

Author:

Levy Jeremy^ORCID,Álvarez Daniel^ORCID,del Campo Felix^ORCID,Behar Joachim A^ORCID

Funder

CIBER en Bioingeniería, Biomateriales y Nanomedicina

Technion Machine Learning & Intelligent Systems Center

Publisher

IOP Publishing

Subject

Physiology (medical),Biomedical Engineering,Physiology,Biophysics

Link

https://iopscience.iop.org/article/10.1088/1361-6579/abf5ad/pdf

Reference35 articles.

1. Global and regional estimates of COPD prevalence: systematic review and meta-analysis;Adeloye;J. Glob. Health,2015

2. Extracting lung function measurements to enhance phenotyping of chronic obstructive pulmonary disease (COPD) in an electronic health record using automated tools;Akgün;PLoS One,2020

3. Assessment of automated analysis of portable oximetry as a screening test for moderate-to-severe sleep apnea in patients with chronic obstructive pulmonary disease;Andrés-Blanco;PLoS One,2017

4. From sleep medicine to medicine during sleep: a new paradigm;Behar;Sleep,2019

5. Validity of an automated telephonic system to assess COPD exacerbation rates;Bischoff;Eur. Respir. J.,2012

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1. An explainable artificial intelligence framework for risk prediction of COPD in smokers;BMC Public Health;2023-11-06

2. The 2023 wearable photoplethysmography roadmap;Physiological Measurement;2023-11-01

3. Deep learning for obstructive sleep apnea diagnosis based on single channel oximetry;Nature Communications;2023-08-12

4. Machine learning-enabled risk prediction of chronic obstructive pulmonary disease with unbalanced data;Computer Methods and Programs in Biomedicine;2023-03

5. Descriptive characteristics of continuous oximetry measurement in moderate to severe covid-19 patients;Scientific Reports;2023-01-09

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