Article

Development and Validation of a Localized Large Language Model for Preoperative Anesthesia Planning: Protocol for a Retrospective Observational Study and Clinical Turing Test

2026-08-31

Abstract excerpt

<title>Abstract</title> <p> <bold>Background:</bold> The preoperative anesthesia assessment requires rapid synthesis of complex patient data, a process prone to cognitive fatigue and inter-provider variability. While large language models (LLMs) show promise in medical education and exam preparation, their efficacy in generating safe, localized clinical management plans remains unvalidated. This study proposes...

Identifiers and source

Literature Corpus work: a5fc0c1b-4032-54ba-920c-7c2eae98cae4
DOI: 10.21203/rs.3.rs-10855923/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Click a neighbor to travelStep 1 · 12 closest

Development and Validation of a Localized Large Language Model for Preoperative Anesthesia Planning: Protocol for a Retrospective Observational Study and Clinical Turing TestDOI 10.21203/rs.3.rs-10855923/v1Read

Retrieval Augmented Generation for 10 Large Language Models and its Generalizability in Assessing Medical FitnessSemantic proximity Read

Towards Inpatient Discharge Summary Automation via Large Language Models: A Multidimensional Evaluation with a HIPAA-Compliant Instance of GPT-4o and Clinical Expert AssessmentSemantic proximity Read

Generative Artificial Intelligence versus Anesthesia-Intensive Care Resident Physicians: Performance in Clinical Case Analysis Using the R-IDEA ScoreSemantic proximity Read

Automated Prediction of Radiological Protocols Using Retrieval Augmented GenerationSemantic proximity Read

An interdisciplinary, randomized, single-blind evaluation of state-of-the-art large language models for their implications and risks in medical diagnosis and managementSemantic proximity Read

Language-dependent diagnostic safety of medical AI systems: a cross-lingual benchmarking and prospective clinical studySemantic proximity Read

The Inefficacy of Artificial Intelligence Large Language Models in Healthcare: A Clinical and Statistical PerspectiveSemantic proximity Read

Clinical Knowledge and Reasoning Abilities of AI Large Language Models in Anesthesiology: A Comparative Study on the ABA ExamSemantic proximity Read

Understanding the Inner Workings of Large Language Models in MedicineSemantic proximity Read

Development and Testing of a Novel Large Language Model-Based Clinical Decision Support Systems for Medication Safety in 12 Clinical SpecialtiesSemantic proximity Read

Understanding the Inner Workings of Large Language Models in MedicineSemantic proximity Read

A Systematic Review of Large Language Models in Medical Specialties: Applications, Challenges and Future DirectionsSemantic proximity Read