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Following the publication of the above paper, a concerned reader drew to the Editor's attention that Fig. 3 on p. 664, showing TUNEL assay data relating to apoptosis of the cell line under investigation in this paper, contained apparent anomalies, including repeated patternings of certain cells both within and between the data panels, such that it would have been difficult to have attributed these anomalies to coincidence.
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Department of Life Sciences, Imperial College London, London W12 0BZ, United Kingdom.
Large language models' performances regarding common patient questions about osteoarthritis: A comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and perplexity.
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Department of Orthopaedics and Traumatology, Faculty of Medicine, The Chinese University of Hong Kong, 999077 Hong Kong, China; Center for Neuromusculoskeletal Restorative Medicine (CNRM), The Chinese University of Hong Kong, 999077 Hong Kong, China. Electronic address:
Background: Large Language Models (LLMs) have gained much attention and, in part, have replaced common search engines as a popular channel for obtaining information due to their contextually relevant responses. Osteoarthritis (OA) is a common topic in skeletal muscle disorders, and patients often seek information about it online. Our study evaluated the ability of 3 LLMs (ChatGPT-3.
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Background: As the burden of cardiovascular disease grows, so does the number of cardiac surgeries. Surgery is increasingly performed on older people with comorbidities who are at higher risk of developing perioperative complications such as low cardiac output state (LCOS). Surgery-associated LCOS represents a serious pathology responsible for substantial morbidity and mortality.
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