Predictive business process monitoring refers to the act of making predictions about the
future state of ongoing cases of a business process, based on their incomplete execution …

Early classification of time series has been extensively studied for minimizing class
prediction delay in time-sensitive applications such as medical diagnostic and industrial …

This paper provides a survey of big data analytics applications and associated
implementation issues. The emphasis is placed on applications that are novel and have …

Artificial intelligence (AI)-based rotating machinery fault diagnosis has extreme importance
in the industrial automation and control systems since rotating machinery constitutes …

Early time series classification predicts the class label of a given time series before it is
completely observed. In time-critical applications, such as arrhythmia monitoring in ICU …

Autonomous detection of desired events from large databases using time series
classification is becoming increasingly important in civil engineering as a result of continued …

Background: Medical concepts are inherently ambiguous and error-prone due to human
fallibility, which makes it hard for them to be fully used by classical machine learning …

Early classification of time series is the prediction of the class label of a time series before it
is observed in its entirety. In time-sensitive domains where information is collected over time …

Early classification algorithms help users react faster to their machine learning model's
predictions. Early warning systems in hospitals, for example, let clinicians improve their …

Early classification of time series is prevalent in many time-sensitive applications such as,
but not limited to, early warning of disease outcome and early warning of crisis in stock …