Abstract
The quality of service in healthcare is constantly challengedby outlier events such as pandemics and naturaldisasters. In most cases, such events lead to critical uncertaintiesin decision making, as well as in multiple medicaland economic aspects of a hospital. External (geographical)or internal factors (medical and managerial) at hospitals,lead to shifts in planning, budgeting, and confidencein conventional processes. In some cases, support fromother hospitals becomes inevitable. This manuscript presentsthree intelligent methods that provide data-drivenindicators to help healthcare managers organize their economicsand identify the most optimum plan for resourceallocation and sharing. Using reinforcement learning, geneticalgorithms, traveling salesman, and clustering, weexperimented with different healthcare variables and presentedtools and outcomes that could be applied at healthinstitutes. In this poster, initial experiments are performed;the results are recorded, evaluated, and illustrated.
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