Microsoft has recently unveiled a new tool called Dragon Copilot that is set to make a difference in medical documentation. This advanced artificial intelligence system is capable of listening to conversations between the physician and the patient and can turn them into regular notes. The technology used in this tool originates from NUance, which specializes in audio artificial intelligence and owned Microsoft in 2021.
Dragon Copilot helps doctors spend less time on office work by automating the information registration process. It offers capabilities such as producing notes in different languages and the natural recording of conversations. It also enables medical data to search for reliable sources and perform tasks such as writing post -visit reports or summarizing clinical evidence.
Joe Pietro, one of Microsoft’s senior executives in the health sector, said the purpose of designing the tool is to reduce administrative pressures on the treatment staff. He believes that physicians can focus more on patients’ needs using this technology. Microsoft’s internal studies show that physicians who have used NUance technology have felt less burnout. Also, 93 % of patients said they had a better experience of their treatment process.
Microsoft is not the only actor in the field. Google Claud has recently announced that its artificial intelligence tools are being used in the field of health to make intelligent assistants to identify possible patients’ problems. On the other hand, the US Food and Drug Administration (FDA) released guidelines last year for evaluating artificial intelligence technologies in medicine and emphasizing its advantages, warning of the possibility of producing inaccurate information by some systems.
Microsoft assures that Dragon Copilot operates based on a secure structure in accordance with health standards. Using secure chat and regulations, this tool is trying to provide users with accurate and reliable outputs and take a step towards developing responsible artificial intelligence.
Source: Microsoft
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