Empirical phenotyping in coupled patient+care systems: Generating low-dimensional categories for hypothesis-driven investigation of mechanically-ventilated patients.

ABSTRACT:

Background

Analyzing patient data under current mechanical ventilation (MV) management processes is essential to develop hypotheses about improvements and to understand MV consequences over time. However, progress is complicated by the complexity of lung-ventilator system (LVS) interactions, patient-care and patient-ventilator heterogeneity, and a lack of classification schemes for observable behavior.

Method

Ventilator waveform data arise from patient-ventilator interactions within the LVS while care processes manage both patient and ventilator settings. This study develops a computational pipeline that segments these joint waveform data and care settings timeseries to phenotype the data generating process. The modular method supports many methodological choices for represe

SUBMITTER: Stroh JN 

PROVIDER: S-EPMC10760265 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature