Abstract-This paper outlines the development a Medical Expert System for the diagnosis and treatment Hypertension in Pregnancy to be used in the Reproductive Health Division, at Moi Teaching and Referral Hospital in Eldoret, Kenya. The Diagnostic and Treatment Expert System for Hypertension in Pregnancy has so far remained at the testing phase of its life cycle and is yet to be implemented. During the research, it was found that there is an acute shortage of specialist obstetricians in the Reproductive Health Division which implies that there is also scarce expert knowledge on the diagnosis and treatment of Hypertension in Pregnancy, yet the condition continues to kill many women of reproductive age in Kenya, hence the need to develop the Medical Expert System (MES) as an expert knowledge sharing tool to be used by other medical personnel within the Reproductive Health Division who are not specialists in diagnosis and treatment of Hypertension in Pregnancy.Index Terms-Rule based expert system, medical expert system, medical informatics.

Computational resources have such a significant influence on the operation of any software application, it is therefore important to understand how these applications utilize these resources. Modern resource-intensive enterprise and scientific applications are creating a growing demand for high performance computing infrastructures. They constantly interact with and rely heavily on complex resources. However, they often operate in resource-limited environments yet they often handle massive data, both in size and complexity. Software application services, processes or transactions compete for the much required but scarce resources. This creates the need to improve the existing resource allocation and management issue in such operational environments, as well as propose new ones, if necessary. Software developers try to analyze application operation environment using diverse analysis and design methods. Our aim therefore, is to design a tool that is able to work with a hybrid of adaptive and prediction-based resource management and allocation models while applying the priority based job scheduling algorithm to try and solve the application resource management challenges currently being faced in such environments, even if, partially.

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