Type 2 diabetes mellitus (T2DM) is associated with multi-organ complications, including cardiovascular and renal disease. Fundus photography provides a non-invasive window into systemic microvascular health, and artificial intelligence (AI) has enabled extraction of retinal biomarkers for systemic risk prediction beyond diabetic retinopathy detection. We conducted a methodologically structured scoping review following PRISMA-ScR guidance to map […]
Older adults’ acceptability and perceived barriers to digital health tools integrating nutrition and physical activity: a focus group study
IntroductionThe rapid ageing of the population presents significant public health challenges, particularly in countries with high life expectancy such as Italy. Although nutrition and physical activity are key determinants of healthy ageing, many older adults do not meet recommended guidelines. Mobile health (mHealth) technologies may support healthy behaviors; however, evidence on older adults’ perspectives remains […]
Locally-deployed vs. cloud-based AI in healthcare: evaluating DeepSeek-R1:8b, DeepSeek-R1, and ChatGPT o3-mini-high for complex medical diagnostics
Reasoning large language models are increasingly considered for healthcare-related artificial intelligence applications, but their practical value depends not only on diagnostic accuracy, but also on responsiveness and operational reliability. In this study, we benchmarked six model settings on 1,000 questions from the MedQA dataset: DeepSeek-R1, its distilled 8-billion-parameter local variant DeepSeek-R1:8b, ChatGPT o3-mini-high, and their […]
Big data integration for enhanced epidemiological research: insights and directions from NHLBI’s workshop
The landscape of epidemiological research is experiencing a technological transformation, driven by the rapid expansion of big data and advancements in artificial intelligence (AI) and machine learning (ML). This workshop explored the opportunities and challenges associated with integrating diverse data sources into population-based research at different levels, including electronic health records (EHRs), genomic and omics […]
Trustworthy intelligent rooms: integrating blockchain, federated learning, and data-centric AI for healthcare 4.0
IntroductionIntelligent room systems are experiencing a surge in demand within the Healthcare 4.0 ecosystem. The integration of Federated Learning (FL) and Data-Centric AI has led to substantial enhancements in the predictive capabilities of machine learning models while maintaining data privacy. However, centralized aggregation in FL remains a single point of failure and is vulnerable to […]
AI-driven mental health decision support linked to clinician resilience and preparedness
ObjectivesMental health services are facing unprecedented demand, placing significant pressure on clinicians to conduct timely and effective patient assessments. Rising staff turnover and burnout threatens service quality across many countries. This study examined whether providing clinical information, collected via an artificial intelligence (AI)—enabled decision support tool for mental health assessments in the UK’s National Health […]
Sanofi defends Garijo appointment, says it is ‘fully committed’ to immunology
Sanofi’s first-quarter earnings call with the media on Thursday was an exercise in redirecting the narrative before its new CEO steps in next week. CFO François-Xavier Roger defended the company’s appointment of Merck KGaA’s Belén …
AbbVie makes record investment in North Carolina plant
AbbVie’s $100bn programme of facility investments in the US has continued with a new 185-acre campus in Durham, North Carolina.
Engagement, motivation, or sustained attention? Rethinking the effects of technology in autism
Technology-based interventions for Autism Spectrum Disorder (ASD) are frequently justified on the grounds that digital tools “increase engagement” and “enhance motivation.” However, across domains such as robot-assisted therapy, immersive environments (virtual and augmented reality), and ICT-based educational applications, outcomes labeled as engagement are often derived from observable indicators including gaze, time-on-task, interaction duration, task adherence, […]
Engagement, motivation, or sustained attention? Rethinking the effects of technology in autism
Technology-based interventions for Autism Spectrum Disorder (ASD) are frequently justified on the grounds that digital tools “increase engagement” and “enhance motivation.” However, across domains such as robot-assisted therapy, immersive environments (virtual and augmented reality), and ICT-based educational applications, outcomes labeled as engagement are often derived from observable indicators including gaze, time-on-task, interaction duration, task adherence, […]
Cognitive Alignment At No Cost: Inducing Human Attention Biases For Interpretable Vision Transformers
arXiv:2604.20027v1 Announce Type: cross Abstract: For state-of-the-art image understanding, Vision Transformers (ViTs) have become the standard architecture but their processing diverges substantially from human attentional characteristics. We investigate whether this cognitive gap can be shrunk by fine-tuning the self-attention weights of Google’s ViT-B/16 on human saliency fixation maps. To isolate the effects of semantically relevant […]
Is Four Enough? Automated Reasoning Approaches and Dual Bounds for Condorcet Dimensions of Elections
arXiv:2604.19851v1 Announce Type: cross Abstract: In an election where $n$ voters rank $m$ candidates, a Condorcet winning set is a committee of $k$ candidates such that for any outside candidate, a majority of voters prefer some committee member. Condorcet’s paradox shows that some elections admit no Condorcet winning sets with a single candidate (i.e., $k=1$), […]