How does AI support physicians without replacing their clinical judgment?
AI can prepare notes, reports, follow-up drafts, and coding suggestions while an authorized clinician retains diagnosis, treatment, and clinical approval. The institution defines the review and escalation required for each workflow.
Put the evidence in context
Review the intended task, source information, human checkpoints and observed results together. A benchmark or sandbox result has a defined scope; it does not establish suitability, approval or performance for every institution.
Read the full explanationCare Workspace connects healthcare work such as appointments, reviewed reporting and follow-up. Micromeet Cowork supports team work with digital employees and reusable Skills, including meeting summaries, decisions and task handoffs.
Read the full explanationThe useful boundary is between preparation and clinical judgment. Depending on the configured workflow, AI may transcribe a consultation into a structured draft, assemble information for a Medical Check-Up (MCU) report, prepare a follow-up message, or suggest ICD (International Classification of Diseases) codes. An authorized clinician remains responsible for diagnosis, treatment, and approval of clinical content; administrative staff may approve only the non-clinical actions within their role.
The institution should decide which outputs require review, who is qualified to perform it, and what happens when confidence is low or information conflicts. A draft/approved distinction and review record can support that control, but the exact events captured, audit integrity, retention, and release rules are deployment-specific. The institution, vendor, and subprocessors also retain their respective legal, contractual, data, and security duties.