Meta-research and evidence synthesis require considerable resources. Large language models (#LLMs ) have emerged as promising tools to assist in these processes, yet their performance varies across models, limiting their reliability. Taking advantage of the large availability of small size (<10 billion parameters) open-source LLMs, we implemented an agreement-based framework in which a decision is… Continue reading Beyond human gold standards: A multimodel framework for automated abstract classification and information extraction
Tag: LLMs
Human-large language model collaboration in clinical medicine: a systematic review and meta-analysis
Human- #AI collaboration (H + AI) using large language models ( #LLMs ) offers a promising approach to enhance clinical reasoning, documentation, and interpretation tasks. Following PRISMA 2020 (PROSPERO registration: CRD420251068272), we systematically compared H + AI with human-only (H) workflows, searching four databases through June 28, 2025. Ten peer-reviewed studies met eligibility criteria, with… Continue reading Human-large language model collaboration in clinical medicine: a systematic review and meta-analysis
Effective prompt design for large language models in clinical #practice
Large language models ( #LLMs ) have emerged as transformative healthcare tools for clinical documentation, diagnostic reasoning, and medical education. However, effective utilization requires understanding prompt engineering principles—the strategic design of inputs to optimize performance while mitigating hallucination, bias, and outdated information.MethodsThis narrative review synthesizes evidence from a structured PubMed search through December 2025 using… Continue reading Effective prompt design for large language models in clinical #practice
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