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.
6 articles
Newest firstIn this study, we introduce a novel benchmark comprising over 9,000 real-world, point-of-care, multilingual, and multimodal clinical question-answer pairs sourced from frontline health workers in Nigeria. Using the dataset, we compare local general practitioners to multiple leading open and closed LLMs. Our results reveal several critical insights into the suitability of LLMs as clinical decision support systems i…
Open article record in new tab ↗To characterise the potential learning effects from a GenAI-based clinical decision support tool (CDST), we examined clinician behaviour within a cluster-randomised trial. The tool, AI Consult, parsed clinician notes written (in real-time) to document patient encounters and would raise green, yellow, or red flags to indicate no, potential, or critical risks of harm (respectively) in decisions the clinician made. O…
Open article record in new tab ↗BackgroundLarge language models (LLMs) show promise on healthcare tasks, yet most evaluations emphasize multiple-choice accuracy rather than open-ended reasoning. Evidence from low-resource settings remains limited. MethodsWe benchmarked five LLMs (GPT-4.1, Gemini-2.5-Flash, DeepSeek-R1, MedGemma, and o3) against Kenyan clinicians, using a randomly subsampled dataset of 507 vignettes (from a larger pool of 5,107 c…
Large language models (LLMs) have demonstrated strong performance in medical contexts; however, existing benchmarks often fail to reflect the real-world complexity of low-resource health systems accurately. This study developed a dataset of 5,609 clinical questions contributed by 101 community health workers (CHWs) across four Rwandan districts and compared responses generated by five large language models (LLMs)…
For decades, medical voice dictation and scribe services have boosted productivity in high-resource settings. Yet, they remain virtually absent in low- and middle-income countries (LMICs), where healthcare systems face physician shortages and heavier patient loads, but rely on outdated, paper-based workflows. Digital transformation efforts in these settings often overlook a critical barrier: the limited computer p…
Open article record in new tab ↗BackgroundNon-pharmacological interventions were introduced based on modelling studies which suggested that the English National Health Service (NHS) would be overwhelmed by the COVID-19 pandemic. In this study, we describe the pattern of bed occupancy across England during the first wave of the pandemic, January 31st to June 5th 2020. MethodsBed availability and occupancy data was extracted from daily reports sub…
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