Synthetic healthcare data can appear realistic across a whole population while failing to reproduce important patient subgroups. A recent analysis in BMC Medical Informatics and Decision M
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Clinical artificial intelligence is expanding across specialties, creating a growing challenge for clinicians and health systems that must identify, assess and safely use an increasing num
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Medical imaging files can be manipulated to carry malicious code, creating a route into healthcare systems and exposing sensitive patient data. A recent investigation identified thousands
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Cybersecurity requirements for AI-enabled medical device software increasingly converge on the same core goals but remain unevenly integrated into regulatory and quality systems. A compara
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AI agents are gaining access to sensitive identity systems while many organisations remain uncertain about their ability to recover from an AI-related breach. The State of Identity Securit
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Clinical AI governance is becoming a practical requirement as high-risk systems move from technical validation into routine care. A framework developed at the Institut de Cancérolog
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Cybersecurity should be embedded throughout healthcare procurement, from early planning to supplier oversight and eventual system retirement. New July 2026 guidance from the European Union
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Computer-based work occupies a larger share of emergency physicians’ shifts than direct patient care in an observational assessment of emergency department workflow. A cross-sectiona
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Medical digital twins used to guide clinical interventions require validation that extends beyond conventional measures of predictive accuracy. A framework published in JAMIA Open
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Clinical prediction models can perform well on average while still making incorrect predictions with high confidence, creating risks when their outputs influence clinical decisions. BMC Me
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