2023
DOI: 10.3390/diagnostics14010090
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Validation of a Deep Learning Chest X-ray Interpretation Model: Integrating Large-Scale AI and Large Language Models for Comparative Analysis with ChatGPT

Kyu Hong Lee,
Ro Woon Lee,
Ye Eun Kwon

Abstract: This study evaluates the diagnostic accuracy and clinical utility of two artificial intelligence (AI) techniques: Kakao Brain Artificial Neural Network for Chest X-ray Reading (KARA-CXR), an assistive technology developed using large-scale AI and large language models (LLMs), and ChatGPT, a well-known LLM. The study was conducted to validate the performance of the two technologies in chest X-ray reading and explore their potential applications in the medical imaging diagnosis domain. The study methodology cons… Show more

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Cited by 4 publications
(4 citation statements)
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References 24 publications
(27 reference statements)
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“…The accuracy of LLM outputs is heavily dependent on the quality and diversity of the training data. Generic models not specifically trained on medical data might provide inaccurate responses to medical tasks [13]. Even medically oriented LLMs could have limitations in their representation of certain information [13].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The accuracy of LLM outputs is heavily dependent on the quality and diversity of the training data. Generic models not specifically trained on medical data might provide inaccurate responses to medical tasks [13]. Even medically oriented LLMs could have limitations in their representation of certain information [13].…”
Section: Discussionmentioning
confidence: 99%
“…Generic models not specifically trained on medical data might provide inaccurate responses to medical tasks [13]. Even medically oriented LLMs could have limitations in their representation of certain information [13]. Additionally, the rapid evolution of medical knowledge poses a challenge, as LLMs might not have access to the latest data and guidelines.…”
Section: Discussionmentioning
confidence: 99%
“…Increasing research focuses on developing and validating AI models that can support medical diagnostics, offering tools with high accuracy and clinical utility. For example, a study by Lee et al [13] showed that the KARA-CXR model, developed using advanced AI techniques and large language models, achieved significantly higher diagnostic accuracy in interpreting chest X-ray images compared to ChatGPT. Similarly, innovative machine learning schemes, such as those developed by Al-Karawi et al [42], have demonstrated high effectiveness in identifying COVID-19 infections based on texture analysis of chest X-ray images.…”
Section: Lack Of Attempt To Assess the Cobb Angle By Microsoft Bingmentioning
confidence: 99%
“…Lee et al [ 4 ] evaluate the diagnostic accuracy of two AI techniques, namely KARA-CXR and ChatGPT, in chest X-ray reading. Using 2000 chest X-ray images, their study assessed accuracy, false findings, location inaccuracies, count inaccuracies, and hallucinations.…”
Section: Overview Of the Published Articlesmentioning
confidence: 99%