Predicting Haemodynamic Instability in Critical Congenital Heart Disease Patients: A Proof of Concept

Introduction<br/>Approximately 9 in 1000 children are born with congenital heart disease (CHD), of whom a quarter are classified as critical CHD (CCHD) and require an intervention within their first year. Monitoring these patients in the Paediatric Intensive Care Unit (PICU) is crucial, yet with increasing amounts of data, detecting subtle...

The ICU-Recover Box: Using Smart Technology For Monitoring Health Status After ICU Admission

Patients who are admitted to the Intensive Care Unit (ICU) are extremely ill and at high risk of organ failure and death. Being admitted to the ICU is known to cause long lasting physical, cognitive, and physiological symptoms, which is called Post-Intensive Care syndrome (PICS). To provide better management of PICS, early recognition and...

The Effect of Color Spaces and Spectra on a Strawberry Prediction Model

The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...

Integrating Predictive and Optimization Model for Intelligent Schedule Management based on Real Time ETA Information: A Concept of Machine Learning and Exact Solution in Petrochemical Loading Facility

This study addresses the truck rescheduling problem as the consequence of uncertain arrival time. It proposes an integrated system of predictive model powered by machine learning algorithm and exact optimization model such that it is distinct from most existing literatures in this domain. The uncertainty of truck arrival time is captured as...

Bed Exit Prediction

This report presents a bed exit prediction model using a decision tree classifier, a machine learning method. This system is designed to alarm a caregiver in a nursing home to prevent bed­ falls among institutionalized elderly. For the input of this algorithm, features are derived from four force sensing resistor sensors and six piezoelectric...