Hospitals and clinics in some areas see enormous numbers of people who don't speak the local language well. While human interpreters have been common in exam rooms during patient care, it turns out that…
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Nick Woodier, senior safety investigator at the Health Services Safety Investigations Body (HSSIB) (Credit: HSSIB)
Electronic patient record (EPR) training is often not sufficient to equip staff with the knowledge needed to use systems…
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Medical AI training at Asan Medical Center and more Korea briefs | Healthcare IT News
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Background: Various mental disorders are associated with impaired cognitive control, which is crucial for effective emotion regulation. Cognitive control training has demonstrated promise in enhancing emotion regulation and alleviating distress in disorders characterized by…
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Background: Effective treatments for depression are available, yet many patients do not respond to treatment or experience relapse. Cognitive bias modification aims to ameliorate cognitive biases that contribute to the development and maintenance of…
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Euan McComiskie, health informatics lead at the Chartered Society of Physiotherapists and member of the Digital Health Networks Chief Nursing Information Officer Advisory Panel (Credit: CSP)
A free digital education programme has been launched…
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Why Hospitals Must Focus on Cyber Resilience
The utility of thinking along the lines of a minimum viable hospital becomes clear when considering today’s healthcare environment:
Reliance on technology is absolute. Despite the continued focus on training…
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Dry eye disease (DED) is exacerbated by prolonged screen use, partly due to reduced blink frequency and a higher percentage of incomplete blinks (IB). In this prospective, randomized study, we assessed whether a smartphone‑based…
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The Persistent Sepsis Crisis
For years, the approach to sepsis in acute care settings has followed the same playbook: early warning alerts and standardized care protocols. Healthcare facilities worldwide have invested heavily in these systems,…
Current AI approaches for cardiac diagnosis require condition-specific supervised learning with extensive labeled datasets, leading to fundamental scalability barriers. We developed an ECG-CLIP model, applying contrastive multimodal learning to enable zero-shot cardiac diagnosis from…
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