Introduction Survival period prediction through early diagnosis of cancer has many benefits.
It allows both patients and caregivers to plan resources, time and intensity of care to provide …

The utilisation of smart devices, such as smartwatches and smartphones, in the field of
movement disorders research has gained significant attention. However, the absence of a …

Machine learning algorithms designed to characterize, monitor, and intervene on human
health (ML4H) are expected to perform safely and reliably when operating at scale …

Reproducibility is one of the core dimensions that concur to deliver Trustworthy Artificial
Intelligence. Broadly speaking, reproducibility can be defined as the possibility to reproduce …

Abstract Machine learning (ML) models deployed in healthcare systems must face data
drawn from continually evolving environments. However, researchers proposing such …

Background Despite the increasing number of studies in breast cancer survival prediction,
there is little attention put toward deceased patients and their survival lengths. Moreover …

Background Many clinical datasets are intrinsically imbalanced, dominated by
overwhelming majority groups. Off-the-shelf machine learning models that optimize the …

Machine learning models deployed in healthcare systems face data drawn from continually
evolving environments. However, researchers proposing such models typically evaluate …

Although lung cancer survival status and survival length predictions have primarily been
studied individually, a scheme that leverages both fields in an interpretable way for …

As cancer is the leading global cause of death, an ongoing challenge is predicting an
individual's cancer progression accurately, to facilitate personalized treatment planning …