The challenge of making flexible, standard, and early medical diagnoses is significant.
However, some limitations are not fully overcome. First, the diagnosis rules established by …

Alzheimer's disease (AD) is a very complex disease that causes brain failure, then
eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed …

Apart from the need for superior accuracy, healthcare applications of intelligent systems also
demand the deployment of interpretable machine learning models which allow clinicians to …

Background The diagnosis of many diseases can be often formulated as a decision
problem; uncertainty affects these problems so that many computerized Diagnostic Decision …

The World Health Organization (WHO) indicates that the proportion of the elderly will soon
include nearly a quarter of the world population. Ensuring that health systems are prepared …

The fight against Alzheimer's disease (AD) has become a major issue. We aim to contribute
to this fight by seeking to provide adequate software to assist decision makers in the field of …

Interpretable artificial intelligence (AI), also known as explainable AI, is indispensable in
establishing trustable AI for bench-to-bedside translation, with substantial implications for …

The growing significance of clinical decision support systems (CDSS) has become a positive
factor influential in pushing medical care toward success. It depends on using successful …

Soft computing techniques came into reality to deal effectively with the emerging problems
related to many fields. A medical diagnosis is totally based on human abilities, uncertain …

In this paper, we propose an OWL2 ontology based on SNOMED CT standard medical
terminology. It can provide significant help to support physicians in diabetes risk level …