Evaluating Retrieval-Augmented Generation-Large Language Models for Infective Endocarditis Prophylaxis: Clinical Accuracy and Efficiency

LLMs with RAG provide rapid and accessible support for clinical decision-making. Nonetheless, their outputs are not always accurate and may not fully reflect evolving medical and dental knowledge. It is crucial that clinicians and students approach these tools with digital literacy and caution, ensuring that professional judgment remains central.

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Publication Details

Journal
International Dental Journal
Published
2025-12-25
DOI
https://doi.org/10.1016/j.identj.2025.109344
Citations
1
Primary Topic
Infective Endocarditis Diagnosis and Management
Type
article
Field-Weighted Citation Impact
1.35
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article

Evaluating Retrieval-Augmented Generation-Large Language Models for Infective Endocarditis Prophylaxis: Clinical Accuracy and Efficiency

Vorapat Trachoo, Paak Rewthamrongsris, Thantrira Porntaveetus, Jirayu Burapacheep et al.
1 citations
International Dental Journal
Infective Endocarditis Diagnosis and Management
1.35
article

Evaluating Retrieval-Augmented Generation-Large Language Models for Infective Endocarditis Prophylaxis: Clinical Accuracy and Efficiency

Vorapat Trachoo, Paak Rewthamrongsris, Thantrira Porntaveetus, Jirayu Burapacheep, Zohaib Khurshid, Vivat Thongchotchat
article en
1 citations

Abstract

LLMs with RAG provide rapid and accessible support for clinical decision-making. Nonetheless, their outputs are not always accurate and may not fully reflect evolving medical and dental knowledge. It is crucial that clinicians and students approach these tools with digital literacy and caution, ensuring that professional judgment remains central.

International Dental JournalVol. 76(1)
Chulalongkorn University (TH), Stanford University (US)
Quality Education
Openalex Percentile: Top 13%
Infective Endocarditis Diagnosis and Management
1.35
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