Gene Variant Analysis for the Detection of Hemophilia: A Literature Review

Abstract

Proteins act as clotting factors to stop bleeding at the lesion site. Depending on the type of hemophilia, individuals with hemophilia will have lesser amounts of factor VIII or factor IX than people without it. This implies that people with hemophilia tend to bleed longer after an injury and are more prone to internal bleeding. Predicting hemophilia can be achieved through potential technologies like machine learning. Using these technologies, one can detect and predict the severity of hemophilia, such as mild, moderate, or severe. This study represents recent research on hemophilia and the use of different machine learning techniques (MLT) in this area. The best practices in predicting hemophilia are highlighted in this study and particularly aim at the basic understanding of applying the potential technologies in the prediction of hemophilia and its severity.