TY - JOUR
T1 - Interventional Radiology ex-machina
T2 - impact of Artificial Intelligence on practice
AU - Gurgitano, Martina
AU - Angileri, Salvatore Alessio
AU - Rodà, Giovanni Maria
AU - Liguori, Alessandro
AU - Pandolfi, Marco
AU - Ierardi, Anna Maria
AU - Wood, Bradford J.
AU - Carrafiello, Gianpaolo
N1 - Funding Information:
Supported in part by the Intramural Research Program of the NIH and the NIAID Intramural Targeted Anti-COVID-19 Program. NIH and NVIDIA, Philips, Siemens, and Canon Medical have collaborations in this space or Cooperative Research and Development Agreements.
Funding Information:
This study was not supported by any funding.
Publisher Copyright:
© 2021, Italian Society of Medical Radiology.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Artificial intelligence (AI)
KW - Augmented reality (AR)
KW - Deep learning (DL)
KW - Interventional radiology (IR)
KW - Machine learning (ML)
KW - Virtual reality (VR)
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U2 - 10.1007/s11547-021-01351-x
DO - 10.1007/s11547-021-01351-x
M3 - Review article
AN - SCOPUS:85104778234
VL - 126
SP - 998
EP - 1006
JO - Radiologia Medica
JF - Radiologia Medica
SN - 0033-8362
IS - 7
ER -