Clinical data management systems typically provide caregiver teams with useful information,
derived from large, sometimes highly heterogeneous, data sources that are often changing …

Objectives: To review how health informatics systems based on machine learning methods
have impacted the clinical management of patients, by affecting clinical practice. Methods …

In the emerging field of acoustic novelty detection, most research efforts are devoted to
probabilistic approaches such as mixture models or state‐space models. Only recent studies …

This paper presents a conformal inference method for out-of-distribution testing that
leverages side information from labelled outliers, which are commonly underutilized or even …

With the lack of failure data, class imbalance has become a common challenge in the fault
diagnosis of industrial systems. The oversampling methods can tackle the class-imbalanced …

This paper develops novel conformal methods to test whether a new observation was
sampled from the same distribution as a reference set. Blending inductive and transductive …

Among the renewable energy sources, wind power generation presents competitive costs
and high installation potential in many countries. Ensuring the integrity of the generation …

An outlier probability is the probability that an observation is an outlier. Typically, outlier
detection algorithms calculate real-valued outlier scores to identify outliers. Converting …

One-class SVM (OCSVM) has been widely adopted in many one-class classification (OCC)
application fields. However, when there are outliers in OCC training samples, the OCSVM …

Background The use of spectral imaging within the plant phenotyping and breeding
community has been increasing due its utility as a non-invasive diagnostic tool. However …