Using Large Language Models to Retrieve Critical Data from Clinical Processes and Business Rules by Yunguo Yu, Cesar A. Gomez-Cabello, Svetlana Makarova, Yogesh Parte, Sahar Borna, Syed Ali Haider, Ariana Genovese, Srinivasagam Prabha, Antonio J. Forte

“…This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations. We tested LLaMA 2′s performance in interpreting complex clinical process models, such as Mayo Clinic Care Pathway Models (CPMs), and providing accurate clinical recommendations. …”
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Source Characteristics Influence AI-Enabled Orthopaedic Text Simplification by Saman Andalib, BS, Sean S. Solomon, BS, Bryce G. Picton, BS, Aidin C. Spina, BS, John A. Scolaro, MD, Ariana M. Nelson, MD

“…This study assesses the effectiveness of large language models (LLMs) in simplifying complex language within orthopaedic patient education materials (PEMs) and identifies predictive factors for successful text transformation. …”
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Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study. by Huy Cong Nguyen, Hai Phong Dang, Thuy Linh Nguyen, Viet Hoang, Viet Anh Nguyen

“…This study evaluated six of the latest LLMs as of August 2024, including ChatGPT 4.0 omni (OpenAI), Gemini Advanced 1.5 Pro (Google), Copilot Pro with GPT-4 Turbo (Microsoft), Claude 3.5 Sonnet (Anthropic), Mistral Large 2 (Mistral AI), and Llama 3.1 405b (Meta). χ2 tests were performed to determine whether there were significant differences in the percentages of correct answers among LLMs for both the total sample and each discipline (p < 0.05).…”
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Deploying large language models for discourse studies: An exploration of automated analysis of media attitudes. by Qingyu Gao, Dezheng William Feng

“…This study aims to provide an LLM (Large Language Model)-based method for the discourse analysis of media attitudes, and thereby investigate media attitudes towards China in a Hong Kong-based newspaper. …”
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Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies by Kim Lauper, Denis Mongin, Nils Bürgisser, Samia Mehouachi, Clement P. Buclin, Delphine S. Courvoisier, Etienne Chalot

“…Objectives We propose and test a framework to detect disease diagnosis using a recent large language model (LLM), Meta’s Llama-3-8B, on French-language electronic health record (EHR) documents. …”
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Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison by Zichang Su, Kai Jin, Hongkang Wu, Ziyao Luo, Andrzej Grzybowski, Juan Ye

“…However, a comprehensive assessment of LLMs’ accuracy within specific medical domains is still lacking. …”
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Information extraction from historical well records using a large language model by Zhiwei Ma, Javier E. Santos, Greg Lackey, Hari Viswanathan, Daniel O’Malley

“…In this paper, we present an information extraction workflow based on open-source Llama 2 models and test it on a dataset of 160 well documents. …”
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Exploring the Impact of Large Language Models on Disease Diagnosis by Ibrahim Almubark

“…The review highlighted the widespread use of LLMs, such as GPT-4, ChatGPT, GPT-3.5, and LLaMA, with GPT-4 being the most frequently used in disease diagnostics due to its diverse applications, improved accuracy, and efficiency. …”
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A dataset for evaluating clinical research claims in large language models by Boya Zhang, Alban Bornet, Anthony Yazdani, Philipp Khlebnikov, Marija Milutinovic, Hossein Rouhizadeh, Poorya Amini, Douglas Teodoro

“…CliniFact contains 1,970 instances from 992 unique clinical trials related to 1,540 unique publications. When evaluating LLMs against CliniFact, discriminative models, such as BioBERT with an accuracy of 80.2%, outperformed generative counterparts, such as Llama3-70B, which reached 53.6% accuracy (p-value < 0.001). …”
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Towards evaluating and building versatile large language models for medicine by Chaoyi Wu, Pengcheng Qiu, Jinxin Liu, Hongfei Gu, Na Li, Ya Zhang, Yanfeng Wang, Weidi Xie

“…We evaluate nine leading LLMs, e.g., MEDITRON, Llama 3, Mistral, GPT-4, Claude-3.5, etc. and found that most models struggle with these complex tasks. …”
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Evaluating the Performance of Large Language Models in Predicting Diagnostics for Spanish Clinical Cases in Cardiology by Julien Delaunay, Jordi Cusido

“…This study explores the potential of large language models (LLMs) in predicting medical diagnoses from Spanish-language clinical case descriptions, offering an alternative to traditional machine learning (ML) and deep learning (DL) techniques. …”
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A scientific-article key-insight extraction system based on multi-actor of fine-tuned open-source large language models by Zihan Song, Gyo-Yeob Hwang, Xin Zhang, Shan Huang, Byung-Kwon Park

“…We have developed an article-level key-insight extraction system based on LLMs, calling it ArticleLLM. After evaluating the LLMs against manual benchmarks, we have enhanced their performance through fine-tuning. …”
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Large Language Models for UAVs: Current State and Pathways to the Future by Shumaila Javaid, Hamza Fahim, Bin He, Nasir Saeed

“…Additionally, we summarize the state-of-the-art LLM-based UAV architectures and identify novel opportunities for LLM embedding within UAV frameworks. …”
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Zero-Shot Classification of Art With Large Language Models by Tatsuya Tojima, Mitsuo Yoshida

“…Our experiments demonstrated that the 4-bit quantized Llama-3 70B model, which can run on a local server, achieved the most accurate (over 0.9) automatic annotation of different art forms using LLMs, performing slightly better than the GPT-4o model from OpenAI. …”
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Interpretable machine learning models for predicting skip metastasis in cN0 papillary thyroid cancer based on clinicopathological and elastography radiomics features by Xiaohua Yao, Mingming Tang, Min Lu, Jie Zhou, Debin Yang

“…SHAP analysis identified five key determinants of SLNM: three radiomics features from elastography images, one clinical variable, and one pathological variable.ConclusionOur evaluation highlights the XGBoost model, which integrates elastography radiomics and clinicopathological data, as the most effective ML approach for the prediction of SLNM in cN0 PTC patients with increased risk of LNM. …”
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Traffic Flow Prediction Based on Large Language Models and Future Development Directions by Zhang Muhua, Zhao Wenzheng

“…By leveraging LLMs’ advanced understanding capabilities, R2T-LLM provides more transparent and interpretable predictions. …”
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Which curriculum components do medical students find most helpful for evaluating AI outputs? by William J. Waldock, George Lam, Ana Baptista, Risheka Walls, Amir H. Sam

“…Abstract Introduction The risk and opportunity of Large Language Models (LLMs) in medical education both rest in their imitation of human communication. …”
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Towards the improvement of project team performance based on large language models by Mykyta Rohovyi, Marina Grinchenko

“…How to utilize the power of large language models (LLMs) to identify and improve textual descriptions of tasks? …”
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The Potential Clinical Utility of the Customized Large Language Model in Gastroenterology: A Pilot Study by Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee, Jonghyung Park, Eunsil Kim, Subeen Kim, Minjae Kimm, Seoung-Ho Choi

“…Aim: This study explores the potential clinical utility of two LLMs in the field of gastroenterology: a customized GPT model and a conventional GPT-4o, an advanced LLM capable of retrieval-augmented generation (RAG). …”
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Application of large language models in disease diagnosis and treatment by Xintian Yang, Tongxin Li, Qin Su, Yaling Liu, Chenxi Kang, Yong Lyu, Lina Zhao, Yongzhan Nie, Yanglin Pan, Yuanyuan Ji

“…Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. …”
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