“‘Big 5’ Hospitals Expand In-House AI Adoption”…Seoul St. Mary’s Hospital Pilots CMC GenNote

As major tertiary hospitals in Korea expand the adoption of in-house AI solutions tailored to their own clinical environments, Seoul St. Mary’s Hospital was introduced as a case of piloting CMC GenNote, an upgraded system advanced in collaboration with Puzzle AI. The solution was presented as part of the broader move toward AI-powered EMR automation, supporting real-time conversation capture, summarization, template calling, and chart draft generation.

Expansion of In-House AI Across Major Hospitals

According to the report, major tertiary hospitals are moving beyond fragmented external tools and increasingly adopting AI systems developed or customized for their own hospital networks and clinical workflows. The article links this trend to stronger data protection needs, tighter system integration, EMR automation, and improved clinical efficiency.

CMC GenNote Pilot at Seoul St. Mary’s Hospital

Within this broader trend, Seoul St. Mary’s Hospital was highlighted as piloting CMC GenNote, an enhanced AI voice recognition system jointly advanced with Puzzle AI. The report says the system has been in pilot operation since October 29 in pediatrics, obstetrics and gynecology, endoscopy, and operating rooms.

Real-Time Documentation and Draft Generation

CMC GenNote was described as going beyond simple speech capture. It records conversations between clinicians and patients in real time, summarizes content, calls relevant templates, and generates chart drafts. In that sense, it was presented as a system that connects voice input with actual clinical documentation workflow.

Advanced Medical Speech Recognition for Hospital Environments

The article notes that CMC GenNote can recognize the voice of a specific clinician even in noisy hospital environments and uses an LLM to support documentation that reflects medical terminology. This positions the solution as an example of advanced speech-based documentation designed for real clinical settings.

A Notable Case in the EMR Automation Trend

The case was introduced as part of a broader shift in which major hospitals are adopting AI to reduce documentation burden and improve care efficiency. The article also emphasized that hospitals are increasingly pursuing customized AI systems suited to their own clinical environments and data structures.

This pilot can be read as an example of how medical speech recognition and documentation technology is being applied within the wider trend of hospital-specific AI adoption.

For more details, please refer to the media coverage below.

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Source: Asia Today (https://www.asiatoday.co.kr/)