<?xml version="1.0"?>
<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Radiotherapy department supported by an optimization algorithm for scheduling patient appointments</dc:title><dc:creator>Chavez,	Marcela	(Avtor)
	</dc:creator><dc:creator>Gonzalez,	Silvia	(Avtor)
	</dc:creator><dc:creator>Alvaro,	Ruiz	(Avtor)
	</dc:creator><dc:creator>Patrick,	Duflot	(Avtor)
	</dc:creator><dc:creator>Jansen,	Nicolas	(Avtor)
	</dc:creator><dc:creator>Mlakar,	Izidor	(Avtor)
	</dc:creator><dc:creator>Arioz,	Umut	(Avtor)
	</dc:creator><dc:creator>Šafran,	Valentino	(Avtor)
	</dc:creator><dc:creator>Kolh,	Philippe	(Avtor)
	</dc:creator><dc:creator>Marteyn,	Van Gasteren	(Avtor)
	</dc:creator><dc:subject>appointments</dc:subject><dc:subject>hospital management</dc:subject><dc:subject>optimization algorithm</dc:subject><dc:subject>patient satisfaction</dc:subject><dc:subject>planning</dc:subject><dc:subject>radiotherapy</dc:subject><dc:description>Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difﬁcultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange ﬁxed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efﬁciently. It respects the different treatment Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difﬁcultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange ﬁxed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efﬁciently. It respects the different treatment.</dc:description><dc:date>2025</dc:date><dc:date>2025-02-25 11:03:50</dc:date><dc:type>Neznano</dc:type><dc:identifier>91901</dc:identifier><dc:identifier>UDK: 004.8:616.82/.84</dc:identifier><dc:identifier>COBISS_ID: 227213059</dc:identifier><dc:identifier>DOI: 10.1177/14604582251318252</dc:identifier><dc:identifier>ISSN pri članku: 1741-2811</dc:identifier><dc:language>sl</dc:language></metadata>
