Society of Interventional Radiology
WASHINGTON, DC (March 8, 2017)--Interventional radiologists at the University of California at Los Angeles (UCLA) are using technology found in self-driving cars to power a machine learning application that helps guide patients' interventional radiology care, according to research presented today at the Society of Interventional Radiology's 2017 Annual Scientific Meeting.
The researchers used cutting-edge artificial intelligence to create a "chatbot" interventional radiologist that can automatically communicate with referring clinicians and quickly provide evidence-based answers to frequently asked questions. This allows the referring physician to provide real-time information to the patient about the next phase of treatment, or basic information about an interventional radiology treatment.
"We theorized that artificial intelligence could be used in a low-cost, automated way in interventional radiology as a way to improve patient care," said Edward W. Lee, M.D., Ph.D., assistant professor of radiology at UCLA's David Geffen School of Medicine and one of the authors of the study. "Because artificial intelligence has already begun transforming many industries, it has great potential to also transform health care."
In this research, deep learning was used to understand a wide range of clinical questions and respond appropriately in a conversational manner similar to text messaging. Deep learning is a technology inspired by the workings of the human brain, where networks of artificial neurons analyze large datasets to automatically discover patterns and "learn" without human intervention. Deep learning networks can analyze complex datasets and provide rich insights in areas such as early detection, treatment planning, and disease monitoring.
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