Benchmarking Large Language Models Using a Best Evidence Topic Report in a Patient With Early Non-Small Cell Lung Cancer

There were no major differences between RATS and VATS lobectomy for T1cN0M0 NSCLC apart from shorter LOS following RATS. Current LLMs may not be entirely reliable for answering clinical questions. An LLM-BET protocol could be used as a standardized process to compare LLM outputs for different clinical scenarios, each benchmarked with a BET. It can also be used to analyse outputs of different models of current and future LLMs.

Authors

Institutions

Publication Details

Journal
Interdisciplinary CardioVascular and Thoracic Surgery
Published
2026-02-01
DOI
https://doi.org/10.1093/icvts/ivag038
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Benchmarking Large Language Models Using a Best Evidence Topic Report in a Patient With Early Non-Small Cell Lung Cancer

Peter Tcherveniakov, Nilanjan Chaudhuri, vivek Chaudhuri, Alessandro Brunelli
Interdisciplinary CardioVascular and Thoracic Surgery
Artificial Intelligence in Healthcare and Education
article

Benchmarking Large Language Models Using a Best Evidence Topic Report in a Patient With Early Non-Small Cell Lung Cancer

Peter Tcherveniakov, Nilanjan Chaudhuri, vivek Chaudhuri, Alessandro Brunelli
article en

Abstract

There were no major differences between RATS and VATS lobectomy for T1cN0M0 NSCLC apart from shorter LOS following RATS. Current LLMs may not be entirely reliable for answering clinical questions. An LLM-BET protocol could be used as a standardized process to compare LLM outputs for different clinical scenarios, each benchmarked with a BET. It can also be used to analyse outputs of different models of current and future LLMs.

Interdisciplinary CardioVascular and Thoracic SurgeryVol. 41(2)
University of Leeds (GB), St James's University Hospital (GB), University of Oxford (GB)
Quality Education
Openalex Percentile: Top 65%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.