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Artificial Intelligence (AI) algorithms showcase the potential to steer a paradigm shift in clinical medicine, especially medical imaging. Concerns associated with model generalizability and biases necessitate rigorous external validation of AI algorithms prior to their adoption into clinical workflows. To address the barriers associated with patient privacy, intellectual property, and diverse model requirements, we introduce ClinValAI, a framework for establishing robust cloud-based infrastructures to clinically validate AI algorithms in medical imaging.

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Background: People of African and Caribbean heritage in the UK have a higher prevalence of Type 2 Diabetes (T2D) and poorer health outcomes than white Europeans. Healthy Eating and Active Lifestyles for Diabetes Online (HEAL-D Online) is a co-designed, culturally tailored T2D self-management programme for black African and Caribbean adults, which, due to online delivery, is well positioned for spread. This qualitative evaluation uses the Exploration-Preparation-Implementation-Sustainment (EPIS) framework to explore factors affecting scale-up from delivery and commissioning perspectives.

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Objectives: To determine the reliability of the Bleeding Assessment Scale in critically Ill Children (BASIC) definition of bleeding severity in a diverse cohort of critically ill children.

Design: Prospective cohort study.

Setting: Eight mixed PICUs in the Netherlands, Israel, and the United States.

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Objectives: To assess the feasibility and acceptability of delivering Healthy Eating and Active Lifestyles for Diabetes (HEAL-D) Online.

Intervention: HEAL-D Online-a 7-week culturally tailored type 2 diabetes educational programme delivered using online platform.

Setting: Programme delivered by a London NHS trust, with patients referred from primary care healthcare professionals via a central booking system.

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Purpose: (i) Characterize ultra-processed food (UPF) intakes in toddlerhood and mid-childhood, including identifying principal UPF sub-groups and associations with nutrient profile; (ii) explore stability and change in UPF intake between toddlerhood and mid-childhood.

Methods: Data were from children in the UK Gemini twin cohort at 21 months (n = 2,591) and 7 years (n = 592) of age. UPF intakes were estimated using diet diaries and Nova classification.

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