Machine learning and lean six sigma for targeted patient-specific quality assurance of volumetric modulated arc therapy plans

Background and purpose: Radiotherapy plans with excessive complexity exhibit higher uncertainties and worse patient-specific quality assurance (PSQA) results, while the workload of measurement-based PSQA can impact the efficiency of the radiotherapy workflow. Machine Learning (ML) and Lean Six Sigma...

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Podrobná bibliografie

Hlavní autoři:	Nicola Lambri, Damiano Dei, Giulia Goretti, Leonardo Crespi, Ricardo Coimbra Brioso, Marco Pelizzoli, Sara Parabicoli, Andrea Bresolin, Pasqualina Gallo, Francesco La Fauci, Francesca Lobefalo, Lucia Paganini, Giacomo Reggiori, Daniele Loiacono, Ciro Franzese, Stefano Tomatis, Marta Scorsetti, Pietro Mancosu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2024-07-01
Edice:	Physics and Imaging in Radiation Oncology
Témata:	Machine learning Lean six sigma Quality Radiotherapy Clinical risk management
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2405631624000873
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