PROBABILISTIC GRAPHICAL MODELS APPLICATIONS IN MEDICAL RESEARCHES

Abstract

The use of intelligent systems in medical research and practice has a long history, becoming an essential support tool nowadays. In this paper, we investigated and presented an overview of the Probabilistic Graphical Models, as well as some applications of them in medical research. We explored these approaches because they are widely used for inference in environments of uncertainty, especially for inter-causal reasoning. Such techniques are established as safe and complete inference mechanisms, which motivated our explanation and analysis. The methods investigated are promising for health research. They can be applied to different types of inference problems, especially causal inference, which is very common in the case of diseases, syndromes, and disorders.