Use of Multimodal Artificial Intelligence in Surgical Instrument Recognition by Syed Ali Haider, Olivia A. Ho, Sahar Borna, Cesar A. Gomez-Cabello, Sophia M. Pressman, Dave Cole, Ajai Sehgal, Bradley C. Leibovich, Antonio Jorge Forte

“…This study evaluates the accuracy of publicly available Large Language Models (LLMs)—ChatGPT-4, ChatGPT-4o, and Gemini—and a specialized commercial mobile application, Surgical-Instrument Directory (SID 2.0), in identifying surgical instruments from images. …”
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The externalization of internal experiences in psychotherapy through generative artificial intelligence: a theoretical, clinical, and ethical analysis by Yuval Haber, Dorit Hadar Shoval, Inbar Levkovich, Dror Yinon, Karny Gigi, Oori Pen, Tal Angert, Zohar Elyoseph, Zohar Elyoseph

“…Recent advances in generative artificial intelligence (GenAI), specifically large language models (LLMs), present new possibilities for therapeutic interventions; however, their integration into core psychotherapy practices remains largely unexplored. …”
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Correlation-guided decoding strategy for low-resource Uyghur scene text recognition by Miaomiao Xu, Jiang Zhang, Lianghui Xu, Wushour Silamu, Yanbing Li

“…Abstract Currently, most state-of-the-art scene text recognition methods are based on the Transformer architecture and rely on pre-trained large language models. However, these pre-trained models are primarily designed for resource-rich languages and exhibit limitations when applied to low-resource languages. …”
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Unleashing the potential of chatbots in mental health: bibliometric analysis by Qing Han, Chenyang Zhao

“…High-frequency terms such as “ChatGPT”, “machine learning”, and “large language models” underscore the current state of research, highlighting the cutting-edge advancements and frontiers in this field.ConclusionsThis study provides an in-depth analysis of the most prominent countries, institutions, publications, collaboration status, and research topics associated with utilization of chatbots in mental health over the last decade. …”
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Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records by Judit M. Wulcan, Kevin L. Jacques, Mary Ann Lee, Samantha L. Kovacs, Nicole Dausend, Lauren E. Prince, Jonatan Wulcan, Sina Marsilio, Stefan M. Keller

“…Large language models (LLMs) can extract information from veterinary electronic health records (EHRs), but performance differences between models, the effect of hyperparameter settings, and the influence of text ambiguity have not been previously evaluated. …”
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Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis by Junyu Liu, Qian Niu, Momoko Nagai-Tanima, Tomoki Aoyama

“…Natural language processing techniques and large language models (LLMs) were used for stance analysis of the collected data. …”
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AI versus human-generated multiple-choice questions for medical education: a cohort study in a high-stakes examination by Alex KK Law, Jerome So, Chun Tat Lui, Yu Fai Choi, Koon Ho Cheung, Kevin Kei-ching Hung, Colin Alexander Graham

“…Abstract Background The creation of high-quality multiple-choice questions (MCQs) is essential for medical education assessments but is resource-intensive and time-consuming when done by human experts. Large language models (LLMs) like ChatGPT-4o offer a promising alternative, but their efficacy remains unclear, particularly in high-stakes exams. …”
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What’s Going On With Me and How Can I Better Manage My Health? The Potential of GPT-4 to Transform Discharge Letters Into Patient-Centered Letters to Enhance Patient Safety: Prospe... by Felix Eisinger, Friederike Holderried, Moritz Mahling, Christian Stegemann–Philipps, Anne Herrmann–Werner, Eric Nazarenus, Alessandra Sonanini, Martina Guthoff, Carsten Eickhoff, Martin Holderried

“…However, these letters are often written in professional jargon, making them difficult for patients with limited medical knowledge to understand. Large language models, such as GPT, have the potential to transform these discharge summaries into patient-friendly letters, improving accessibility and understanding. …”
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Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis by Jalil Jalili, PhD, Anuwat Jiravarnsirikul, MD, Christopher Bowd, PhD, Benton Chuter, MD, Akram Belghith, PhD, Michael H. Goldbaum, MD, Sally L. Baxter, MD, Robert N. Weinreb, MD, Linda M. Zangwill, PhD, Mark Christopher, PhD

“…Design: Evaluation of multimodal large language models for reviewing fundus images in glaucoma. …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Secondly, the combination of deep learning and reinforcement learning techniques is expected to empower robots to better interpret environmental patterns, adapt to dynamic changes, and make more effective real-time decisions. Thirdly, large language models will enhance human-robot interaction by enabling natural language commands, improving collaborative operations. …”
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Unveiling GPT-4V's hidden challenges behind high accuracy on USMLE questions: Observational Study by Zhichao Yang, Zonghai Yao, Mahbuba Tasmin, Parth Vashisht, Won Seok Jang, Feiyun Ouyang, Beining Wang, David McManus, Dan Berlowitz, Hong Yu

“…GPT-4V’s accuracy was compared with 2 state-of-the-art large language models, GPT-3.5 Turbo and GPT-4. The quality of the explanations was evaluated by choosing human preference between an explanation by GPT-4V (without hint), an explanation by an expert, or a tie, using 3 qualitative metrics: comprehensive explanation, question information, and image interpretation. …”
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