Early identification of respiratory deterioration in intensive care unit (ICU) patients remains a central clinical challenge. Mechanical intubation is often required with little warning, an
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Magnetic resonance imaging is widely used to assess pancreatic and hepatobiliary disease because it provides high soft-tissue contrast and detailed visualisation of ductal anatomy without e
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Multiphase contrast-enhanced CT (CECT) is widely used to evaluate renal tumours, yet several treatment-relevant factors remain difficult to determine before surgery. Histological subtype, c
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Artificial intelligence is increasingly influencing how breast cancer screening is approached, with growing attention on risk stratification alongside image interpretation. Advances in data
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Preoperative assessment of ground-glass nodules (GGNs) in lung adenocarcinoma (LUAD) remains clinically important because pathological invasiveness can influence both surgical planning and progn1
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Medical practice is shaped by probability. Clinicians are trained to prioritise the most common explanations for symptoms, an approach that supports efficiency and safety in everyday care. For p1
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Artificial intelligence is becoming more visible across healthcare organisations, with measurable changes in reported use over time. Biweekly responses from a large business survey spanning Sept1
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Artificial intelligence is becoming increasingly visible across oncology services, from diagnostics and treatment planning to administrative workflows. As these technologies move closer to
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Healthcare systems increasingly rely on large, diverse datasets to support evidence-based practice and the development of artificial intelligence. In paediatric care, such datasets are ofte
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Artificial intelligence is increasingly embedded in medical imaging workflows, with software-based tools now routinely supporting image analysis, detection and workflow prioritisation. Whil
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