TEE4EHR: Transformer event encoder for better representation learning in electronic health records.

Irregular sampling of time series in electronic health records (EHRs) is one of the main challenges for developing machine learning models. Additionally, the pattern of missing values in certain clinical variables is not at random but depends on the decisions of clinicians and the state of the patient. Point process is a mathematical framework for analyzing event sequence data consistent with irregular sampling patterns.

Steps parameters of elderly patients hospitalised for an acute medical illness in a Swiss University Hospital: a monocentric observational pilot-study.

Background: Objective mobility goals for elderly hospitalised medical patients remain debated. We therefore studied steps parameters of elderly patients hospitalised for an acute illness, to determine goals for future interventional trials and medical practice.

Methods: Observational study conducted from February to November 2018 in a medical ward of the Lausanne University Hospital, Switzerland.

Fractal temporal organisation of motricity is altered in major depression.

Objective: Motor changes in major depression (MD) may represent potential markers of treatment response. Physiological rhythms (heart rate/gait cycle/hand movements) have been recently shown to be neither random nor regular but to display a fractal temporal organisation, possibly reflecting a unique central "internal clock" control. Sleep and mood circadian rhythm modifications observed in MD also suggest a role for this "internal clock".