Kuidas me hindame kliinilise tehisintellekti hallutsinatsiooniriski

Notati tõenduslugu ei ole maagiline täpsusprotsent. See on läbipaistev metoodika: eralda kliinilised faktid esimesena, koosta märkmed nendest faktidest, näita arstile toorest konteksti ning kontrolli iga väljundit tõendite alusel.

Hindamismeetod

1. Build the reference facts

A reviewer reads the encounter material and creates a reference set of clinical facts: symptoms, negatives, medication changes, assessment, plan, safety-netting, and coding-relevant details.

2. Compare transcript-direct output

We generate a note from transcript-style input and mark unsupported statements, missing high-salience facts, incorrect attribution, and invented certainty.

3. Compare FactsContext output

We generate documentation from extracted facts and review whether each sentence is supported by a visible fact. The clinician-facing fact list is evaluated as part of the output, not hidden.

4. Record limits, not magic numbers

We do not publish fake accuracy percentages. Each evaluation note includes dataset scope, review date, known limitations, and examples of what the system still requires clinicians to verify.

Mida hindajad märgivad

Unsupported clinical assertion

Wrong medication, dose, frequency, or route

Missing red-flag negative or safety-net advice

Wrong diagnosis certainty: possible vs established

Wrong speaker attribution

Unsupported ICD-10 suggestion

Clinician-visible evidence for each key statement

Facts reusable for notes, codes, referrals, and patient instructions

Kuupäevaga sisemärkus

Praegune hindamismärkus, 2026-07-01: see leht dokumenteerib meetodi ja kvalitatiivsed näited, mida kasutatakse FactsContexti arhitektuuri hindamiseks. See ei väida välist valideerimist ega universaalset täpsust. Järgmine tõendusetapp peaks olema pimendatud, erialade lõikes stratifitseeritud ülevaade, kus andmestiku suurus, hindajate kokkulangevus ja põhjendamata väidete osakaal avatakse avalikult.

Faktide eraldamine vs otse transkriptsioonipõhine genereerimine

Medication change discussed twice

Otse transkriptsioonist tulenev risk

“Increase amlodipine to 10 mg and stop lisinopril.” The transcript contained a correction: the clinician first considered stopping lisinopril, then decided to continue it after reviewing renal function.

FactsContexti väljund

Facts: amlodipine increased to 10 mg daily; lisinopril continued; renal function normal; review in 6 weeks. Note generated from those facts only.

Miks see on oluline

Transcript-direct generation can smooth over corrections. FactsContext preserves the final decision as a discrete fact before writing.

Negative finding matters

Otse transkriptsioonist tulenev risk

“No neurological symptoms.” The actual encounter only documented no saddle anesthesia and no bladder symptoms; leg radiation was present.

FactsContexti väljund

Facts: left leg radiation to calf; SLR positive left; no saddle anesthesia; no bladder or bowel symptoms. Note keeps the negatives specific.

Miks see on oluline

Broad negative statements are risky. The fact list keeps the clinical context granular and reviewable.

Code suggestion requires evidence

Otse transkriptsioonist tulenev risk

Suggested J44.1 for COPD exacerbation without showing the symptom or treatment evidence.

FactsContexti väljund

Facts: increased breathlessness, purulent sputum, prednisolone burst, antibiotics started. Suggested J44.1 with those facts as evidence.

Miks see on oluline

The code is easier to verify because the reason for the suggestion is visible, not buried in prose.

Teadaolevad piirangud

Clinician review remains mandatory. Notat drafts; clinicians verify and sign.

The method reduces unsupported statements by architecture, but no clinical AI should claim zero hallucinations.

Small internal evaluations are useful for engineering direction, not a substitute for external clinical validation.

Specialty, language, audio quality, speaker overlap, and local coding rules can change performance.

Loe tõendust ja kontrolli seejärel oma fakte.

Hindamismeetod on lihtne, sest toode on loodud kontrollitavaks: faktid enne, märkus pärast, kliiniline ülevaatus alati.

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