Article

Evaluating Accuracy and Reasoning Capabilities of Large Language Models for Acute Ischemic Stroke Management

2025-09-05

Abstract excerpt

<h4>Background</h4> Acute ischemic stroke (AIS) management has evolved substantially over the past two decades, with mechanical thrombectomy adding complexity that requires specialized centers. As many patients initially present to primary care facilities, rapihtmld and accurate triage is critical. Large language models (LLMs) may help bridge expertise gaps, especially where stroke specialists are not immediately...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e47d83aa-cb34-56bc-8f9c-33f12f2a8045
DOI: 10.1101/2025.09.03.25335060

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Evaluating Accuracy and Reasoning Capabilities of Large Language Models for Acute Ischemic Stroke ManagementDOI 10.1101/2025.09.03.25335060Read

Cross-Model Variability in Large Language Model Triage Behavior for Potential Stroke SymptomsSemantic proximity Read

Large Language Models in Stroke Management: A Review of the LiteratureSemantic proximity Read

Prompting is All You Need: How to Make LLMs More Helpful for Clinical Decision SupportSemantic proximity Read

Large Language Models in Clinical Neurology: A Systematic ReviewSemantic proximity Read

Development and evaluation of a structured large language model-based pipeline for automated ICHI coding using neurosurgical request formsSemantic proximity Read

Confidence-linked and uncertainty-based staged framework for phenotype validation using large language models.Semantic proximity Read

Assessing the Limitations of Large Language Models in Clinical Practice Guideline-concordant Treatment Decision-making on Real-world DataSemantic proximity Read

A Novel Framework for Evaluating the Clinical Reasoning Process of Large Language Models: A Comparative Study in NephrologySemantic proximity Read

Artificial Intelligence - Large Language Models (LLMs) and Agentic AI in Clinical Decision Support in Outpatient, General Practice and Acute Settings: A Systematic Review of Diagnostic Accuracy, Comparative Efficacy, Clinical Outcomes and Implementation FactorsSemantic proximity Read

Evaluating the AI Potential as a Safety Net for Diagnosis: A Novel Benchmark of Large Language Models in Correcting Diagnostic ErrorsSemantic proximity Read

Hybrid Intelligence in Oncology: Superior Accuracy and Convergence of Large Language Models Over Human Experts in InterpretingSemantic proximity Read

Dissecting clinical reasoning failures in frontier artificial intelligence using 10,000 synthetic casesSemantic proximity Read