Abstract Recently, Artificial Intelligence (AI) has been used widely in medicine and health
care sector. In machine learning, the classification or prediction is a major field of AI. Today …

This paper provides a literature review in clinical decision support systems (CDSSs) with a
focus on the way knowledge bases are constructed, and how inference mechanisms and …

Background In recent years, outcome prediction models using artificial neural network and
multivariable logistic regression analysis have been developed in many areas of health care …

BACKGROUND: Diagnosing acute appendicitis clinically is still difficult. We developed
random forests, support vector machines, and artificial neural network models to diagnose …

Conventional clinical decision support systems are generally based on a single classifier or
a simple combination of these models, showing moderate performance. In this paper, we …

Globally, the rate of preterm births are increasing, thus resulting in significant health,
development and economic problems. Current methods for the early detection of such births …

AIM: To develop and evaluate an effective classification approach without biochemical
parameters to identify those at high risk of T2DM in rural adults. METHODS: A cross …

Head computed tomography (CT) is the gold standard in emergency departments (EDs) to
evaluate mild traumatic brain injury (mTBI) patients, especially for paediatrics. Data-driven …

Background Within the trauma system, the emergency department (ED) is the hospital's first
contact and is vital for allocating medical resources. However, there is generally limited …

Background A database for hepatocellular carcinoma (HCC) patients who had received
hepatic resection was used to develop prediction models for 1-, 3-and 5-year disease-free …