Artificial intelligence is increasingly embedded across healthcare research, clinical decision support and operational planning, intensifying demand for large, diverse and well-curated data
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Artificial intelligence is becoming embedded in healthcare operations through tools such as ambient listening, productivity features and diagnostic algorithms. As these capabilities expand,
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Large language models (LLMs) are increasingly embedded in healthcare workflows, supporting activities ranging from clinical decision support and question answering to education and research
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Endovascular thrombectomy can reduce disability after ischaemic stroke caused by large vessel occlusion, but access depends on rapid imaging interpretation and efficient transfer to centres
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Artificial intelligence is widely associated with gains in diagnostics, drug discovery and administrative efficiency, yet its application to interpersonal capability is becoming an importan
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Neurodegenerative diseases involve sustained, gradual degeneration of vulnerable neurons and their connections. They can affect cognition, sensation, socioemotional processing, motor function an1
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Vision-language models (VLMs) are being explored for clinically oriented image interpretation across multiple modalities, yet their behaviour degrades when images contain artefacts that are
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The rapid expansion of virtual care during COVID-19 has accelerated interest in virtual hospital-at-home models that deliver hospital-level care in people’s homes through remote monitoring,
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Clinical decisions are often made with incomplete evidence in notes and records, which increases the risk of error when key findings are missing or inconclusive. Diagnosis support that simp
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Clinical prediction models increasingly inform how likely outcomes are discussed for individual patients during clinical decision-making. A single predicted risk can look precise, yet the u
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