Purpose: Artificial intelligence (AI) plays a central role in building decision supporting systems (DSS), and its application in healthcare is rapidly increasing. The aim of this study was to define the role of AI in healthcare, with main focus on radiation oncology (RO) and interventional radiotherapy (IRT, brachytherapy). Artificial intelligence in interventional radiation therapy: AI in RO has a large impact in providing clinical decision support, data mining and advanced imaging analysis, automating repetitive tasks, optimizing time, and modelling patients and physicians’ behaviors in heterogeneous contexts. Implementing AI and automation in RO and IRT can successfully facilitate all the steps of treatment workflow, such as patient consultation, target volume delineation, treatment planning, and treatment delivery. Conclusions: AI may contribute to improve clinical outcomes through the application of predictive models and DSS optimization. This approach could lead to reducing time-consuming repetitive tasks, healthcare costs, and improving treatment quality assurance and patient’s assistance in IRT.
Fionda, B., Boldrini, L., D'Aviero, A., Lancellotta, V., Gambacorta, M. A., Kovacs, G., Patarnello, S., Valentini, V., Tagliaferri, L., Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): State of art and future perspectives, <<JOURNAL OF CONTEMPORARY BRACHYTHERAPY>>, 2020; 12 (5): 497-500. [doi:10.5114/jcb.2020.100384] [http://hdl.handle.net/10807/198602]
Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): State of art and future perspectives
Boldrini, Luca;Gambacorta, Maria Antonietta;Kovacs, Gyorgy;Valentini, Vincenzo;Tagliaferri, Luca
2020
Abstract
Purpose: Artificial intelligence (AI) plays a central role in building decision supporting systems (DSS), and its application in healthcare is rapidly increasing. The aim of this study was to define the role of AI in healthcare, with main focus on radiation oncology (RO) and interventional radiotherapy (IRT, brachytherapy). Artificial intelligence in interventional radiation therapy: AI in RO has a large impact in providing clinical decision support, data mining and advanced imaging analysis, automating repetitive tasks, optimizing time, and modelling patients and physicians’ behaviors in heterogeneous contexts. Implementing AI and automation in RO and IRT can successfully facilitate all the steps of treatment workflow, such as patient consultation, target volume delineation, treatment planning, and treatment delivery. Conclusions: AI may contribute to improve clinical outcomes through the application of predictive models and DSS optimization. This approach could lead to reducing time-consuming repetitive tasks, healthcare costs, and improving treatment quality assurance and patient’s assistance in IRT.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.