This paper proposes a three-phase framework to leverage hospital tracking data of patient
visits while designing healthcare layouts with pod structures. The first phase proposes a …

Clinical pathways (CPs) are standardized, typically evidence-based health care processes.
They define the set and sequence of procedures such as diagnostics, surgical and therapy …

Time series motif discovery is the task of extracting previously unknown recurrent patterns
from time series data. It is an important problem within applications that range from finance …

Time series motif discovery is the task of extracting previously unknown recurrent patterns
from time series data. It is an important problem within applications that range from finance …

Process Mining is the discovery of business processes from log files. One application is
ensuring conformance to prescribed processes or business rules. Since businesses operate …

Repositories of health records are collections of events with varying number and sparsity of
occurrences within and among patients. Although a large number of predictive models have …

Frequent episode discovery is one of the methods used for temporal pattern discovery in
sequential data. An episode is a partially ordered set of nodes with each node associated …

Prescription of conflicting concurrent medications, polypharmacy, is recognised as a
significant problem in the UK, but its extent is not fully known. We combined a process …

This paper describes an approach to constructing a probabilistic process model
representing knowledge worker activity out of a log of primitive events, such as e-mails, web …

This paper presents an approach to automatically discovering the contexts that a knowledge
worker is working in and the different types of actions the knowledge worker is executing …