We evaluated the ability of three leading LLMs (GPT-4o, Gemini 2.0 Experimental, and Claude 3.5 Sonnet) to recognize human facial expression using the NimStim dataset. GPT and Gemini matched or exceeded human performance, especially…
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Recent advances in artificial intelligence, particularly large language models (LLMs), show promise for mental health applications, including the automated detection of depressive symptoms from natural language. We fine-tuned a German BERT-based LLM to predict…
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While large language models (LLMs) hold promise for transforming clinical healthcare, current comparisons and benchmark evaluations of large language models in medicine often fail to capture real-world efficacy. Specifically, we highlight how key discrepancies…
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Generative AI models, including large language models (LLMs) and vision-language models (VLMs), are increasingly used to interpret medical images and answer clinical questions. However, their responses often include inaccuracies; therefore, safety measures like medical…
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Generative artificial intelligence is revolutionizing digital twin development, enabling virtual patient representations that predict health trajectories, with large language models (LLMs) showcasing untapped clinical forecasting potential. We developed the Digital Twin—Generative Pretrained Transformer (DT-GPT),…
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Over 25 million U.S. patients with a non-English language preference face unsafe care because discharge instructions and other materials are rarely translated in time. Advances in translation assisted by large language models can close…
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Patients with diabetes are at increased risk of comorbid depression or anxiety, complicating their management. This study evaluated the performance of large language models (LLMs) in detecting these symptoms from secure patient messages. We…
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“Using data sets of attacker-generated commands and responses, these models are trained to mimic server behaviors convincingly. Techniques such as supervised fine-tuning, prompt engineering and low-rank adaptations help tailor these models for specific tasks,”…
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The Driving Force Behind Cloud Repatriation
Although only 8%-9% of organizations intend to implement full workload repatriation, the cost and regulatory challenges driving the trend are real, according to IDC’s recent Server and Storage Workloads…
Professor Kamila Hawthorne, chair of the Royal College of GPs (Credit: Grainge Photography)
A study has suggested that AI should be used to support the delivery of primary care, after chatbots outperformed GPs based…
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