Evidence Receipt. Related Resources.
Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent
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Page Freshness
Signal Canvas proof surface
Canonical route: /signal-canvas/human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent
- Proof freshness
- stale
- Proof status
- unverified
- Display score
- 8/10
- Last proof check
- 2026-04-02
- Score updated
- 2026-04-02
- Score fresh until
- 2026-05-02
- References
- 0
- Source count
- 0
- Coverage
- 17%
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent
Canonical ID human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent | Route /signal-canvas/human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agentMCP example
{
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"mode": "paper",
"paper_ref": "human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent",
"query_text": "Summarize Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Human-AI Co-reasoning for Clinical Diagnosis with Evidence-Integrated Language Agent",
"normalized_query": "2603.10492",
"route": "/signal-canvas/human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent",
"paper_ref": "human-ai-co-reasoning-for-clinical-diagnosis-with-evidence-integrated-language-agent",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Preparing verified analysis
Dimensions overall score 8.0
GitHub Code Pulse
No public code linked for this paper yet.
Claim map
- Evidencepartial
PULSE attained expert-competitive accuracy, outperforming residents and junior specialists while matching senior specialist performance at both Top@1 and Top@4 thresholds.
ImplicationpartialDirectly stated in abstract with clear comparative performance metrics
Verificationpartialpartial
- Evidencepartial
Unlike physicians, whose accuracy declined with disease rarity, PULSE maintained stable performance across incidence tiers.
ImplicationpartialDirectly stated in abstract with clear comparative finding about performance patterns
Verificationpartialpartial
- Evidencepartial
The agent also exhibited adaptive reasoning, increasing output length with case difficulty in a manner analogous to the longer deliberation observed among expert clinicians.
ImplicationpartialDirectly stated in abstract with clear behavioral pattern described
Verificationpartialpartial
- Evidencepartial
When used collaboratively, PULSE enabled physicians to correct initial errors and broaden diagnostic hypotheses.
ImplicationpartialDirectly stated in abstract with clear benefit of collaboration
Verificationpartialpartial
- Evidencepartial
but also introduced risks of automation bias.
ImplicationpartialDirectly stated in abstract as a limitation of the collaborative approach
Verificationpartialpartial
- Evidencepartial
We present PULSE, a medical reasoning agent that combines a domain-tuned large language model with scientific literature retrieval to support diagnostic decision-making in complex real-world cases.
ImplicationpartialDirectly stated in abstract as the core technical approach
Verificationpartialpartial
- Evidencepartial
The study explores both serial and concurrent collaboration workflows, revealing that PULSE offers robust support across common and rare presentations.
ImplicationpartialDirectly stated in abstract with clear finding about workflow evaluation
Verificationpartialpartial
- Evidencepartial
To evaluate its capabilities, we curated a benchmark of 82 authentic endocrinology case reports encompassing a broad spectrum of disease types and incidence levels.
ImplicationpartialDirectly stated in abstract with specific benchmark details
Verificationpartialpartial
