Understanding published unstructured textual data using traditional text mining approaches
and tools is becoming a challenging issue due to the rapid increase in electronic open …

Machine learning is an established and frequently used technique in industry and
academia, but a standard process model to improve success and efficiency of machine …

Data mining is one of the extensively researched areas in computer science and information
technology owing to the wide influence exhibited by this computational technique on diverse …

The lives of many thousands of children born premature or ill at term around the world have
been saved by those who work within neonatal intensive care units (NICUs). Modern-day …

Public healthcare has a history of cautious adoption for artificial intelligence (AI) systems.
The rapid growth of data collection and linking capabilities combined with the increasing …

There is a lack of specific and detailed framework for conducting data mining analysis in
medicine. Cross Industry Standard Process for Data Mining (CRISP-DM) presents a …

The high demand for radiotherapy services, combined with the limited capacity of available
resources, patient unpunctuality, and series of appointments, makes Patient Appointment …

Background: In order to remain active and productive, older adults with poor health require a
combination of advanced methods of visual monitoring, optimization, pattern recognition …

Given the exponential availability of data in health centers and the massive sensorization
that is expected, there is an increasing need to manage and analyze these data in an …

This paper presents a framework for process mining in critical care. The framework uses the
CRISP-DM model, extended to incorporate temporal and multidimensional aspects (CRISP …