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Freeman T, Rodriguez-Esteban R, Gottowik J, Yang X, Erpenbeck VJ, Leddin M
A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A neural network approach for understanding patient experiences of chronic obstructive pulmonary disease (COPD) through a social media listening study
Tobe Freeman;
Raul Rodriguez-Esteban;
Juergen Gottowik;
Xing Yang;
Veit J. Erpenbeck;
Mathias Leddin
ABSTRACT
The abundance of online content contributed by patients is a rich source of insights about the lived experience of disease. We present a novel neural network approach to identify and explore a lexicon of community words and phrases used by patients to describe their symptoms, and show its utility for the life-threatening chronic lung disease COPD. Our findings demonstrate the potential of neural networks to gain a quantitative patient-focused understanding about how each distinct COPD symptom contributes to the burden of chronic and acute respiratory illness. This approach can be readily applied to other disease areas in which there exists sufficient online content contributed by patients and caregivers.
Citation
Please cite as:
Freeman T, Rodriguez-Esteban R, Gottowik J, Yang X, Erpenbeck VJ, Leddin M
A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content