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, […]
Essential Oil-enhanced digital hypnotherapy for subclinical generalized anxiety: a study protocol for a randomized controlled trial
BackgroundSubsyndromal generalized anxiety is highly prevalent and associated with impaired well-being, elevated stress, and functional limitations, yet affected individuals often do not meet criteria for guideline-based treatment. Scalable, low-threshold digital interventions that target psychophysiological regulation may help address this gap. Guided self-hypnosis and aromatherapy using essential oils have each demonstrated anxiolytic and relaxation-promoting effects. Combining […]
The MediVoice implementation journey: ambient artificial intelligence for clinical documentation
Healthcare systems are increasingly turning to ambient Artificial Intelligence (AI) scribes to reduce documentation burden and lighten clinicians’ cognitive load. In this brief research report, we introduce MediVoice, an ambient AI scribe developed and implemented within the National University Health System, Singapore. MediVoice was piloted across multiple clinical settings and rapidly evaluated through Plan–Do–Study–Act cycles. […]
Exploration of wearable sensor measures associated with panic attacks differs across mental health conditions
Panic attacks (PAs) are acute anxiety episodes that are pervasive, with one in 10 individuals having experienced a PA in the past year. PAs impair daily functioning and are associated with an increase in emergency room visits and suicide attempts. Despite their impact, the unpredictable nature of PAs makes them challenging to manage. PAs are […]
Beyond the algorithm: embedding ethics for trustworthy AI in radiology and oncology
BackgroundArtificial intelligence (AI) in radiology and oncology promises improvements in diagnostic accuracy and efficiency yet introduces complex ethical and societal challenges. Governance efforts frequently rely on high-level principles such as trustworthiness and fairness, which risk becoming ineffective when not grounded in specific contexts. This study presents findings from our work on ethical and societal aspects […]
Promotion and preservation of mobility and autonomy in old age through smart rollators—a qualitative study
BackgroundDiseases and health limitations associated with ageing often result in loss of mobility and reduced social participation. The ongoing demographic shift towards an increasingly ageing population, combined with a declining number of healthcare professionals, highlights the need to integrate digital assistive solutions to reduce workload and healthcare costs. Smart rollators (SRs) equipped with sensor-based assistance […]
FDA kicks off review of Roche’s Gazyva for wider lupus use
Roche could be just months away from an FDA approval of Gazyva as the first anti-CD20 therapy for systemic lupus erythematosus.
Italy leads the way on child genetic disease diagnosis
A scheme to hasten the diagnosis of children with genetic disorders is achieving strong results and could be a template for national health systems.
A digital cognitive behavioral therapy program culturally adapted for Spanish-speaking individuals with alcohol use disorder: a stage 1 randomized clinical trial
BackgroundDigital formats are an important tool for making evidence-based therapies for alcohol use, such as cognitive behavioral therapy (CBT), more broadly available, yet only a small percentage are available in Spanish and none with evidence from effectiveness studies with Spanish-speaking individuals. This study evaluated the feasibility and efficacy of adding a culturally-adapted, web-based CBT program […]
Layer-wise MoE Routing Locality under Shared-Prefix Code Generation: Token-Identity Decomposition and Compile-Equivalent Fork Redundancy
arXiv:2604.17182v1 Announce Type: cross Abstract: In LLM-based code generation, multiple code candidates are often generated in parallel from the same prompt — for example, in best-of-N sampling or multi-candidate code completion. These requests can share KV caches through a common prefix, yet the extent to which their Mixture-of-Experts (MoE) expert routing overlaps, and how this […]
HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
arXiv:2604.16499v1 Announce Type: cross Abstract: Black-box adversarial attack on vision-language pre-trained models is a practical and challenging task, as text and image perturbations need to be considered simultaneously, and only the predicted results are accessible. Research on this problem is in its infancy, and only a handful of methods are available. Nevertheless, existing methods either […]
Revisiting Entropy in Reinforcement Learning for Large Reasoning Models
arXiv:2511.05993v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for enhancing the reasoning capabilities of large language models (LLMs). However, the entropy of LLMs usually collapses during RLVR training, leading to premature convergence to suboptimal local minima and hindering further performance improvement. Although various approaches have been […]