Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

Background: Digital clinical measures collected via various digital sensing technologies
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …

Oncoimmunology represents a biomedical research discipline coined to study the roles of
immune system in cancer progression with the aim of discovering novel strategies to arm it …

We introduce a novel deep-learning-based photoacoustic tomography method called
Photoacoustic Tomography Neural Radiance Field (PA-NeRF) for reconstructing 3D …

Depression is a major cause of disability and mortality for young people worldwide and is
typically first diagnosed during adolescence. In this work, we present a machine learning …

Designing Convolutional Neural Networks (CNNs) for a specific task requires not only Deep
Learning expertise but also knowledge of the problem. The goal of Neuroevolution is to find …

The aim of this paper is to perform uni-and multivariate time series classification tasks with
linear law-based feature space transformation (LLT). First, LLT is used to separate the …

The goal of the linear law-based feature space transformation (LLT) algorithm is to assist
with the classification of univariate and multivariate time series. The presented R package …

Background Polysomnography (PSG) is the gold standard for detecting obstructive sleep
apnea (OSA). However, this technique has many disadvantages when using it outside the …

Predicting hypoglycemic events in a timely and accurate manner is critical for the effective
management of Type 1 Diabetes (T1D) and the prevention of its harmful health …