The Nuclear Medicine Scheduling problem consists of assigning patients to a day, in which the patient will undergo the medical check, the preparation, and the actual image detection process. The schedule of the patients should consider their different requirements and the available resources, e.g., varying time required for different diseases and radiopharmaceuticals used, number of injection chairs, and tomographs available. Recently, this problem has been solved using a logic-based approach utilizing the Answer Set Programming (ASP) methodology. However, it may be the case that a computed schedule can not be implemented due to a sudden emergency and/or unavailability of resources, thus rescheduling is needed. In this paper we present an ASP-based approach to solve such situation, that we call Nuclear Medicine Rescheduling problem. Experiments employing real data from a medium size hospital in Italy show that our rescheduling solution provides satisfying results even when the concurrent number of emergencies and unavailability is significant.

Nuclear Medicine Rescheduling Problem: A Logic-based Approach

Dodaro C.;Maratea M.;Marte C.;
2024-01-01

Abstract

The Nuclear Medicine Scheduling problem consists of assigning patients to a day, in which the patient will undergo the medical check, the preparation, and the actual image detection process. The schedule of the patients should consider their different requirements and the available resources, e.g., varying time required for different diseases and radiopharmaceuticals used, number of injection chairs, and tomographs available. Recently, this problem has been solved using a logic-based approach utilizing the Answer Set Programming (ASP) methodology. However, it may be the case that a computed schedule can not be implemented due to a sudden emergency and/or unavailability of resources, thus rescheduling is needed. In this paper we present an ASP-based approach to solve such situation, that we call Nuclear Medicine Rescheduling problem. Experiments employing real data from a medium size hospital in Italy show that our rescheduling solution provides satisfying results even when the concurrent number of emergencies and unavailability is significant.
2024
Answer Set Programming
Digital Health
Logic Programming
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/382281
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