Background: Artificial intelligence (AI) models have been increasingly explored for predicting treatment response to cognitive behavioral therapy (CBT) in patients with anxiety disorders. Identifying potential responders in advance may help inform treatment planning and support clinical decision-making. Although a growing number of studies have applied AI techniques in this context, reported performance estimates vary across […]

Background: Telehealth use surged during the COVID-19 pandemic and has stabilized at levels substantially above prepandemic baselines. However, concerns persist that the digital divide may reproduce or widen disparities in access. Understanding the determinants of telehealth use—and particularly modality choice between video and audio—is essential for designing policies that promote equitable access in the post–public […]

Background: Short-form videos (SFVs) have emerged as a dominant trend in digital content sharing over the past decade, gaining rapid global popularity. An increasing number of studies have explored the association between SFV use and mental health, yet current empirical evidence remains inconsistent. Objective: This study aimed to provide a comprehensive synthesis examining the relationship […]

Background: Cognitive decline across the mild cognitive impairment (MCI)–dementia continuum is a major driver of loss of independence and growing health- and social-care burden. Immersive technologies, such as virtual reality (VR), augmented reality (AR), and Cave Automatic Virtual Environment (CAVE) systems, are increasingly explored as tools to enhance engagement, personalization, and ecological validity in cognitive […]

Background: Parkinson disease (PD) impairs gait, balance, and quality of life, and wearable devices have been proposed to support rehabilitation, but evidence for their clinical efficacy remains uncertain. Objective: This study aimed to evaluate, within the International Classification of Functioning, Disability, and Health (ICF) framework, the effects of wearable-device interventions on gait performance, balance, and […]

ObjectiveThe paper aims to systematically review the literature on the efficacy of virtual reality (VR) based therapies to treat mental health disorders in Randomized Control Trials (RCTs).MethodsAs of January 2,025, three databases were searched using relevant key terms (PsycINFO, PubMed, and Medline) and Rayyan tool. Eligible studies were English-language RCTs of VR-based interventions with a […]

IntroductionElectronic health record (EHR) systems present clinicians with vast repositories of clinical information, creating a significant cognitive burden where critical details are easily overlooked. While Large Language Models (LLMs) offer transformative potential for data processing, they face significant limitations in clinical settings, particularly regarding context grounding and hallucinations. Current solutions typically isolate retrieval methods, focusing […]

arXiv:2603.16410v1 Announce Type: cross Abstract: Creative plot generation presents a fundamental challenge for language models: transforming a concise premise into a coherent narrative that sustains global structure, character development, and emotional resonance. Although recent Large Language Models (LLMs) demonstrate strong fluency across general-purpose tasks, they typically require preference alignment to perform well on specialized domains […]

arXiv:2603.16567v1 Announce Type: cross Abstract: As large language models (LLMs) have proliferated, disturbing anecdotal reports of negative psychological effects, such as delusions, self-harm, and “AI psychosis,” have emerged in global media and legal discourse. However, it remains unclear how users and chatbots interact over the course of lengthy delusional “spirals,” limiting our ability to understand […]

arXiv:2603.01406v1 Announce Type: cross Abstract: Neural PDE solvers are often described as learning solution operators that map problem data to PDE solutions. In this work, we argue that this interpretation is generally incorrect when boundary conditions vary. We show that standard neural operator training implicitly learns a boundary-indexed family of operators, rather than a single […]

arXiv:2603.00170v3 Announce Type: replace-cross Abstract: Craniofacial Superimposition is a forensic technique for identifying skeletal remains by comparing a post-mortem skull with ante-mortem facial photographs. A critical step in this process is Skull-Face Overlay (SFO). This stage involves aligning a 3D skull model with a 2D facial image, typically guided by cranial and facial landmarks’ correspondence. […]

arXiv:2510.07842v2 Announce Type: replace-cross Abstract: Small language models (SLMs) are crucial for applications with strict latency and computational constraints, yet achieving high performance remains challenging. Knowledge distillation (KD) can transfer capabilities from large teacher models, but existing methods face a dilemma: off-policy distillation provides high-quality supervision but suffers from exposure bias (training inference mismatch), while […]