Objective The proper handling of missing values is critical to delivering reliable estimates
and decisions, especially in high-stakes fields such as clinical research. In response to the …

The emphasis on fairness in predictive healthcare modeling has increased in popularity as
an approach for overcoming biases in automated decision-making systems. The aim is to …

Early prediction of mortality and risk of deterioration in COVID-19 patients can reduce
mortality and increase the opportunity for better and more timely treatment. In the current …

Multiple Sclerosis (MS) is a chronic disease developed in the human brain and spinal cord,
which can cause permanent damage or deterioration of the nerves. The severity of MS …

Background: The COVID-19 infection is a novel virus that mainly targets the respiratory
system via specific receptors without any coronavirus-targeted therapies. Many efforts have …

Mechanical ventilation (MV) is a crucial intervention in the intensive care unit (ICU) for
severely ill patients. However, it can potentially contribute to lung damage due to the …

Introduction During COVID‐19 pandemic, artificial neural network (ANN) systems have been
providing aid for clinical decisions. However, to achieve optimal results, these models …

Introduction: Predicting acute respiratory insufficiency due to coronavirus disease 2019
(COVID-19) can diminish the severe complications and mortality associated with the …

BACKGROUND: Accurately predicting the intubation risk in COVID-19 patients at the
admission time is critical to optimal use of limited hospital resources, providing customized …

Background: Owing to the shortage of ventilators, there is a crucial demand for an objective
and accurate prognosis for 2019 coronavirus disease (COVID-19) critical patients, which …