Microsoft has unveiled Dragon Copilot, an AI system specifically designed for the healthcare sector. Among its many capabilities, the system can listen to clinical visits and generate corresponding notes. Dragon Copilot integrates voice input and ambient listening technologies developed by Nuance, the AI speech company acquired by Microsoft in 2021.
According to Microsoft, this system streamlines document processing through features like "multilingual ambient note-taking" and natural language input. Its AI assistant is capable of conducting "universal medical information searches" from reliable sources and automating tasks such as "conversational orders, note-taking, clinical evidence summaries, referral letters, and post-visit summaries."
The Vice President of Microsoft's Health and Life Sciences Solutions and Platforms division stated that the system aims to "reduce the administrative burden on healthcare professionals," enabling them to focus more on patient care. Microsoft’s research indicates that healthcare workers using Nuance technology, which underpins Dragon Copilot, reported reduced burnout levels, with 93% of patients noting a "better overall experience."
Microsoft is not alone in providing AI tools for the healthcare industry. In a recent blog post, Google Cloud highlighted how healthcare organizations are leveraging its AI products, such as creating medical assistant AIs to identify patient health risks and utilizing the multimodal image search feature of its newly launched Vertex AI Search for Healthcare.
Last year, the U.S. Food and Drug Administration (FDA) released considerations regarding generative AI devices in healthcare, pointing out both their potential benefits and the risks of model hallucinations. A study last year found that Nambla’s medical transcription software, developed using OpenAI Whisper technology, exhibited this issue in certain scenarios. Microsoft emphasized its commitment to "developing responsibly designed AI," stating that Dragon Copilot’s functionalities are built on secure data environments and incorporate clinical, conversational, and compliance safeguards tailored to the healthcare domain to ensure the accuracy and safety of AI outputs.
