Background Trauma-induced coagulopathy (TIC) is a disorder that occurs in one-third of
severely injured trauma patients, manifesting as increased bleeding and a 4X risk of …

Hidden Markov models are stochastic models in which the observations are assumed to
follow a mixture distribution, but the parameters of the components are governed by a …

In this paper, we propose a novel data representation-classification model learning
algorithm. The model is a convolutional neural network (CNN), and we learn its parameters …

Trauma mortality prediction from electronic health records (EHRs) with machine learning
models has received growing attention in medical fields, but EHRs in different hospitals and …

Statistical methods, and in particular deep learning models, have achieved remarkable
success in computer vision, speech recognition, and natural language processing due to the …

The rapid advancement of deep learning has significantly impacted the medical domain,
benefitting various applications including clinical decision-making, personalized treatment …

In this paper, a novel demodulation structure in high-frequency (HF) channel is introduced
and studied. Frequency-offset estimation, fractionally spaced adaptive equalization and …

Multiple organ failure (MOF) is a severe syndrome with a high mortality rate among Intensive
Care Unit (ICU) patients. Early and precise detection is critical for clinicians to make timely …

Significant modern advances in faster and cheaper measurement techniques for biological
processes has led to an explosion in the availability of biological data, from the clinical scale …

Trauma is one of the main causes of hospitalization. Time is of the essence in diagnosis and
treatment of trauma patients with severe injuries. To assist in decision-making, we propose a …