Readable research linked to original sources
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Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
Loading articles data…
Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
7 articles
Newest firstBackgroundLarge language models (LLMs) are increasingly deployed in healthcare, where they may adopt different stakeholder perspectives, yet the effect of role-prompting on clinical ethical reasoning remains poorly characterized. MethodsWe evaluated three frontier LLMs: Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro across 25 ethically complex medical cases. Each model responded from three stakeholder perspectives (…
Open article record in new tab ↗Clinical decision-making is a critical competency for nurses, particularly in resource-constrained healthcare systems where frontline practitioners must integrate clinical knowledge, judgment, and contextual constraints to ensure optimal patient outcomes. Although prior research highlights the benefits of artificial intelligence (AI)-supported learning and individual competencies, it largely assumes a direct relat…
Open article record in new tab ↗BackgroundMultiple long-term conditions (MLTC) are increasingly common and place significant strain on healthcare systems designed around single-organ conditions, often resulting in fragmented and reactive care for people living with MLTC. There is limited understanding of how health care professionals (HCPs) make decisions for and with individuals with MLTC at the point of hospital presentation. This study examin…
BackgroundBiases held by healthcare practitioners can shape clinical interactions, leading to discrimination and poor patient outcomes. Traditional methods, such as vignettes or self-report measures, often lack ecological validity. ObjectiveWe evaluated a novel VR simulation designed to explore bias and discrimination in clinical decision-making. MethodsThirty-five healthcare practitioners across 14 NHS trusts com…
Explainable Artificial Intelligence (XAI) is crucial in healthcare as it helps make intricate machine learning models understandable and clear, especially when working with diverse medical data, enhancing trust, improving diagnostic accuracy, and facilitating better patient outcomes. This paper thoroughly examines the most advanced XAI techniques used in multimodal medical datasets. These strategies include pertur…
Open article record in new tab ↗BackgroundGenerative Pre-trained Transformer 4 (GPT-4) has demonstrated strong performance in standardized medical examinations but has limitations in real-world clinical settings. The newly released multimodal GPT-4o model, which integrates text and image inputs to enhance diagnostic capabilities, and the multimodal o1 model, which incorporates advanced reasoning, may address these limitations. ObjectiveThis stud…
Open article record in new tab ↗BackgroundMultimorbidity, the coexistence of two or more chronic medical conditions, poses significant challenges for healthcare systems in sub-Saharan Africa (SSA), where single-disease-focused approaches currently predominate. Despite the rising burden of multimorbidity in SSA region, data on its clinical management in hospitals is limited. This study aimed to explore healthcare worker experiences in the managem…