Allisone

An AI scribe typically works in four steps:

• Capture: a phone, computer or room microphone records the consultation after the patient is informed or consents.
• Transcription: speech recognition converts audio to text and separates speakers.
• Summarization: a language model extracts relevant content and drafts a note in the chosen format, such as a SOAP note, sometimes with codes or orders suggested.
• Review: the clinician edits and signs the draft, which is then filed in the EHR, often through an integration.

Each step can introduce errors, so final responsibility for the note stays with the clinician. Ask vendors whether audio is stored, whether data is used to train models, and how fabricated or missing content is measured.

Hallucination is when a generative AI tool produces content that sounds plausible but is false or unsupported by its inputs, such as a symptom, medication or exam finding that was never mentioned in a consultation.

It matters most in documentation, summarization and question-answering tools, because errors can be copied into the medical record. Common safeguards are:

• Clinician review and sign-off of every generated note or summary.
• Links from generated text back to the source audio or record.
• Vendor testing that measures omission and fabrication rates in realistic conditions.
• Clear policies on what the tool must not be used for.

WHO's guidance on large multi-modal models highlights inaccurate or false outputs as a key risk.

AI image reconstruction and denoising use deep learning to produce clearer images from raw scanner data or to reduce noise and artifacts, for example in CT or MRI. Vendors often position these tools as supporting lower-dose or faster scanning protocols.

Unlike detection software, these tools change the image the clinician reads rather than adding a finding. Questions to ask include:

• Is the function built into the scanner or a separate software product?
• Which scanners, protocols and body regions is it authorized for?
• How was diagnostic image quality evaluated, and could fine detail be lost or altered?

These functions are typically regulated as part of the imaging device or as image processing software, depending on the product and market.