Interventional Radiology ex-machina: impact of Artificial Intelligence on practice
| Autor: | Bradford J. Wood, Marco Pandolfi, Giovanni Maria Rodà, Salvatore Alessio Angileri, Alessandro Liguori, Anna Maria Ierardi, Gianpaolo Carrafiello, Martina Gurgitano |
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| Rok vydání: | 2020 |
| Předmět: |
Service (systems architecture)
Augmented reality (AR) Process (engineering) Virtual reality Radiology Interventional Artificial intelligence (AI) Interventional radiology (IR) 030218 nuclear medicine & medical imaging Machine Learning 03 medical and health sciences Vascular and Interventional Radiology 0302 clinical medicine Artificial Intelligence Medicine Humans Radiology Nuclear Medicine and imaging Virtual reality (VR) Artificial neural network business.industry Deep learning General Medicine Machine learning (ML) Mixed reality 030220 oncology & carcinogenesis Informatics Deep learning (DL) Augmented reality Artificial intelligence business Algorithms |
| Zdroj: | La Radiologia Medica |
| ISSN: | 1826-6983 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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