The alarms of medical devices are a matter of concern in critical and perioperative care. The
frequent false alarms not only are a nuisance for patients and caregivers but can also …

The high number of false positive alarms has long been known to be a serious problem in
critical care medicine–yet it remains unresolved. At the same time, threats to patient safety …

Robust versions of the exponential and Holt–Winters smoothing method for forecasting are
presented. They are suitable for forecasting univariate time series in the presence of outliers …

Our state-of-the-art methods study hive weight and predict bee health and colony condition
using advanced machine learning tools trained with unlabeled data. By integrating …

The concept of breakdown point was introduced by Hampel [Ph. D. dissertation (1968), Univ.
California, Berkeley; Ann. Math. Statist. 42 (1971) 1887–1896] and developed further by …

Alarms in medical devices are a matter of concern in critical and perioperative care. The
high rate of false alarms is not only a nuisance for patients and caregivers, but can also …

Online‐monitoring systems in intensive care are affected by a high rate of false threshold
alarms. These are caused by irrelevant noise and outliers in the measured time series data …

We develop and test a robust procedure for extracting an underlying signal in form of a time-
varying trend from very noisy time series. The application we have in mind is online …

In this study, robust parametric regression methods are applied to temperature and
precipitation time series in Switzerland and the trend results are compared with trends from …

Research in severe traumatic brain injury (TBI) has historically been limited by studies with
relatively small sample sizes that result in low power to detect small, yet clinically meaningful …