Abstract Machine learning technologies have seen increased application to the healthcare
domain. The main drivers are openly available healthcare datasets, and a general interest …

Continuous renal replacement therapy (CRRT) is widely utilized to support critically ill
patients with acute kidney injury. Artificial intelligence (AI) has the potential to enhance …

Diagnosing and mitigating changes in model fairness under distribution shift is an important
component of the safe deployment of machine learning in healthcare settings. Importantly …

The demand for emergency department (ED) services is increasing across the globe,
particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have …

Continual learning denotes machine learning methods which can adapt to new
environments while retaining and reusing knowledge gained from past experiences. Such …

Use of consensus criteria, standard definitions and common data models could facilitate
access to machine learning-ready data sets for external validation. The lack of …

A health-related (HR) profile is a set of multiple health-related items recording the status of
the patient at different follow-up times post-stroke. In order to support clinicians in designing …

Coronavirus disease 2019 (COVID-19) has strained healthcare systems worldwide.
Predicting COVID-19 severity could optimize resource allocation, like oxygen devices and …

Objective Weaning is an essential issue in critical care. This study explores the efficacy of
multitask learning models in predicting successful weaning in critically ill ventilated patients …

Early identification of Mild Cognitive Impairment (MCI) subjects who will eventually progress
to Alzheimer Disease (AD) is challenging. Existing deep learning models are mostly single …