Abstract
In a modern Diagnostic Imaging Department, managing the schedule of exams is a complex task. Surprisingly, it is still done mostly manually, without a clear, explicit and formally defined objective or target function to achieve.
In this work we propose an efficient approach for optimising the exploitation of available resources. In particular, we provide an objective function, that considers the aspects that have to be optimised, and introduce a two-steps approach for scheduling diagnostic activities. Our experimental analysis shows that the proposed technique can easily scale on large and complex Imaging Departments, and generated allocation plans have been positively evaluated by human experts.
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Gatta, R. et al. (2015). On the Efficient Allocation of Diagnostic Activities in Modern Imaging Departments. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 2015. Lecture Notes in Computer Science(), vol 9273. Springer, Cham. https://doi.org/10.1007/978-3-319-23485-4_10
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DOI: https://doi.org/10.1007/978-3-319-23485-4_10
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