Modeling Clinical Decision Support based on Artificial Neural Network: Optimization of Sickle Cell Treatment

AUTHOR(S):

Eustache Muteba A., Nikos Mastorakis

TITLE

Modeling Clinical Decision Support based on Artificial Neural Network: Optimization of Sickle Cell Treatment

ABSTRACT

Sickle cell disease (SCD) is the monogenic disease that causes complex multisystem red blood cell disorders leading sufferers to life-threatening acute dysfunctions and chronic complications. In practice, comprehensive SCD care is essential and makes it possible to limit complications and reduce early mortality. With so-called precision medicine, there are curative therapies for SDC such as hematopoietic stem cell transplants and gene therapy but which require significant financial means. Means that are not always available to ordinary people, especially in developing countries. This is where solutions for optimizing therapies based on Artificial Intelligence methods intervene. The paper present an approach of SDC treatment optimization based on Artificial Neural Network (ANN). A big data containing cases of sickle cell patients will be used for previous medical decision analysis to produce indicator performance that enables optimal drug therapy.

KEYWORDS

Sickle cell disease, Treatment optimization, Artificial Neural Network, Medical decision support

Cite this paper

Eustache Muteba A., Nikos Mastorakis. (2024) Modeling Clinical Decision Support based on Artificial Neural Network: Optimization of Sickle Cell Treatment. International Journal of Medical Histology and Embryology, 2, 1-6