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Gurgitano M, Angileri SA, Rodà GM, Liguori A, Pandolfi M, Ierardi AM, Wood BJ, Carrafiello G. Interventional Radiology ex-machina: impact of Artificial Intelligence on practice. LA RADIOLOGIA MEDICA 2021; 126:998-1006. [PMID: 33861421 PMCID: PMC8050998 DOI: 10.1007/s11547-021-01351-x] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 03/24/2021] [Indexed: 12/17/2022]
Abstract
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic. AI was mainly introduced via artificial neural networks, developed in the early 1950s, and with its evolution into "computational learning models." Machine Learning analyzes and extracts features in larger data after exposure to examples; Deep Learning uses neural networks in order to extract meaningful patterns from imaging data, even deciphering that which would otherwise be beyond human perception. Thus, AI has the potential to revolutionize the healthcare systems and clinical practice of doctors all over the world. This is especially true for radiologists, who are integral to diagnostic medicine, helping to customize treatments and triage resources with maximum effectiveness. Related in spirit to Artificial intelligence are Augmented Reality, mixed reality, or Virtual Reality, which are able to enhance accuracy of minimally invasive treatments in image guided therapies by Interventional Radiologists. The potential applications of AI in IR go beyond computer vision and diagnosis, to include screening and modeling of patient selection, predictive tools for treatment planning and navigation, and training tools. Although no new technology is widely embraced, AI may provide opportunities to enhance radiology service and improve patient care, if studied, validated, and applied appropriately.
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Affiliation(s)
- Martina Gurgitano
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia.
| | - Salvatore Alessio Angileri
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia
| | - Giovanni Maria Rodà
- Postgraduation School in Radiodiagnostics, Università Degli Studi di Milano, via Festa del Perdono, 20122, Milan, Italy
| | - Alessandro Liguori
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia
| | - Marco Pandolfi
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia
| | - Anna Maria Ierardi
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia
| | - Bradford J Wood
- Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, National Institutes of Health, 10 Center Dr., Room 1C-341, MSC 1182, Bethesda, MD, 20892, USA
| | - Gianpaolo Carrafiello
- Operative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, via Francesco Sforza 35, 20122, Milan, Italia
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
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