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ARXIV:2604.25415 · MEDICAL AI · SUBMITTED 29 APR · 02:44 UTC · FRESHNESS STALE
ARXIV:2604.25415MEDICAL AISUBMITTED 29 APR · 02:44 UTCFRESHNESS STALEVeith Weilnhammer · Lennart Luettgau · Christopher Summerfield · Viknesh Sounderajah · Elise Wilkinson · Virginia Corno · +1 at arXiv
Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations.
Opportunity summary
Pain Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts,…
AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than…
ScienceToStartup currently rates this 6.0/10 on the public viability pass. All results were confirmed relative to clinician consensus labels from 50 medical doctors. Code availability is flagged in the production record; the public repository…
Medical AI moved forward this cycle; last verified April 2026. Public score 6.0/10. Production flags indicate code availability.
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Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations.
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Paper Pack
10.48550/arXiv.2604.25415Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations.
Abstract
AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than from objective findings. We evaluated the performance of 15 frontier AI chatbots on psychiatric triage from realistic single-message disclosures using 112 clinical vignettes, each paired with 1 of 4 original benchmark triage labels: A, routine; B, assessment within 1 week; C, assessment within 24 to 48 hours; and D, emergency care now. Vignettes covered 9 psychiatric presentation clusters and 9 focal risk dimensions, organized into 28 presentation-by-risk groups. Each group contributed 4 distinct vignettes, with 1 vignette at each triage level. Each vignette was rendered as a realistic human-authored conversational query, and the AI chatbots were tasked with assigning a triage label from that disclosure. Emergency under-triage occurred in 23 of 410 level D trials (5.6%), and all under-triaged emergencies were reassigned to level C urgency. Across target models, average accuracy ranged from 42.0% to 71.8%. Accuracy was highest for level D vignettes (94.3%) and lowest for level B vignettes (19.7%). Mean signed ordinal error was positive (+0.47 triage levels), indicating net over-triage. Dispersion was highest around the middle triage levels. All results were confirmed relative to clinician consensus labels from 50 medical doctors. When presented with user messages containing sufficient clinical information, frontier AI chatbots thus recognized psychiatric emergencies as requiring urgent medical assessment with near-zero error rates, yet showed marked over-triage for low and intermediate risk presentations.
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Dimensions overall score 6.0
PROBLEM
Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and...
METHOD
AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than from objective find...
RESULT
ScienceToStartup currently rates this 6.0/10 on the public viability pass. All results were confirmed relative to clinician consensus labels from 50 medical doctors. Code availability is flagged in the production record; the public repository link still needs proof alignment.
WHY NOW
Medical AI moved forward this cycle; last verified April 2026. Public score 6.0/10. Production flags indicate code availability.
Abstract-backed public claims while anchored extraction refreshes.
Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than from objective findings.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
AI chatbots are increasingly used for health advice, but their performance in psychiatric triage remains undercharacterized. Psychiatric triage is particularly challenging because urgency must often be inferred from thoughts, behavior, and context rather than from objective findings.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 6.0/10 on the public viability pass. All results were confirmed relative to clinician consensus labels from 50 medical doctors. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Medical AI moved forward this cycle; last verified April 2026. Public score 6.0/10. Production flags indicate code availability.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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Evaluating 15 frontier AI chatbots on psychiatric triage, this study reveals high accuracy for emergencies but significant over-triage for lower-risk presentations.
Segment
Medical AI
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