Machine Learning Characterization of COPD Subtypes

<p>Systemic Cytokine Profiles of CD4+ T Lymphocytes Correlate with Clinical Features and Functional Status in Stable COPD</p>

“…Systemic manifestations in COPD are diverse and affect patients differently, making them a heterogeneous population, 43 in which individuals are distinguished in relation to biological, clinical, and functional characteristics. 44 In an attempt to identify subgroups of patients, in order to act more precisely, the correlation of biomarkers with clinical and functional characteristics of patients with stable COPD has been explored.…”

Artificial Intelligence in COPD: New Venues to Study a Complex Disease

“…Several other studies have provided evidence for machine-learning driven COPD subtypes that have consolidated the understanding of COPD as both discrete and continuum processes with unique biological characteristics 74,75 . These examples show how data-driven approaches can be used to postulate new hypotheses related to the natural history of COPD.…”

“…Connecting the imaging phenotype with genetic and molecular features in a hypothesis-free way can enable the exploration of novel endophenotypes that could lead to exploring the disease in new directions that can be hard to elucidate with our current understanding of the disease 2 . Although these venues are highly speculative, they hold much promise as the integration of information has been an effective way to improve the understanding of diseases 75 . The same way the advent of imaging changed how many diseases were approached from the research end to the clinical side, AI offers a new paradigm for data integration in COPD with potential ever lasting effects.…”

Integrating Genetics and Omics to Understand Chronic Obstructive Pulmonary Disease

“…Different Omics data types may be more relevant for different subtypes (subsets of COPD subjects with a shared pathobiological mechanism) of the heterogeneous COPD syndrome. A major limitation is that despite extensive efforts with unsupervised clustering analysis 18 , visual and quantitative CT analysis 19 , and transcriptomic-based clustering efforts 20 , there is still not a consensus regarding COPD subtypes. One generally accepted distinction in COPD is that subjects with AAT deficiency have unique clinical and biological features consistent with a COPD subtype.…”