Attackers can use them to inject arbitrary prompts, exfiltrate personal user information, bypass safety mechanisms, and take other malicious actions.
Pfizer said to have matched Novo’s $10bn bid for Metsera
The battle for obesity drug developer Metsera rumbles on, with Pfizer reported to have now matched Novo Nordisk’s $10 billion offer.
Efficacy of digital technology-based interventions for reducing caregiver burden and stress: a systematic review and meta-analysis
BackgroundDemographic aging and increasing dependency associated with chronic diseases have intensified the caregiving responsibilities of family members, often leading to significant burden and stress. Digital technology-based interventions have emerged as promising strategies to support family caregivers, yet their effectiveness remains inconsistent across studies.MethodA systematic review and meta-analysis was conducted following JBI methodology and PRISMA guidelines. […]
Improvements in physical activity and depression symptoms: an observational study of users of a multi-modal digital mental health platform
BackgroundModerate-to-vigorous physical activity (MVPA) and depression symptoms have a longstanding, inverse relationship. This short-term study examined the patterns of MVPA and prevalence of depression symptoms among adults seeking care from an employer-sponsored, multi-modal digital mental health platform.MethodsAdults (n = 755) with access to the platform enrolled in an online, observational study over 3 months. Baseline and longitudinal […]
Adopting machine learning to predict breast cancer patients adherence with lifestyle recommendations and quality of life outcomes
IntroductionHealthy lifestyle behaviors and improved quality of life have been associated with better prognoses in breast cancer survivors. However, sustaining behavioral changes remains challenging; therefore, identifying effective components of lifestyle education programs is essential to enhance adherence, improve quality of life, and facilitate their integration into clinical practice. This study aimed to predict patient adherence […]
Simulated virtual reality experiences for predicting early treatment response in panic disorder
BackgroundPanic disorder (PD) is a disabling anxiety condition in which early improvement during treatment can predict better long-term outcomes.ObjectivesThis study investigated whether a newly developed virtual reality-based assessment tool, the Virtual Reality Assessment of Panic Disorder (VRA-PD), can help predict early treatment response in individuals with PD.MethodsIn total, 52 participants, including 25 patients diagnosed with […]
Feasibility and efficacy of mobile app implementation among patients with acute myocardial infarction enrolled in coordinated cardiac rehabilitation program
IntroductionCardiovascular diseases (CVD), notably acute myocardial infarction (AMI), persist as a leading cause of global mortality despite advances in clinical management. Coordinated cardiac rehabilitation (CR) programs, such as the Coordinated Patient Care Program after Myocardial Infarction (MC-AMI), have demonstrated substantial reductions in mortality rates. However, optimizing outpatient care within these programs remains a challenge due […]
Uncovering Code Insights: Leveraging GitHub Artifacts for Deeper Code Understanding
arXiv:2511.03549v1 Announce Type: cross Abstract: Understanding the purpose of source code is a critical task in software maintenance, onboarding, and modernization. While large language models (LLMs) have shown promise in generating code explanations, they often lack grounding in the broader software engineering context. We propose a novel approach that leverages natural language artifacts from GitHub […]
Visualization Biases MLLM’s Decision Making in Network Data Tasks
arXiv:2511.03617v1 Announce Type: cross Abstract: We evaluate how visualizations can influence the judgment of MLLMs about the presence or absence of bridges in a network. We show that the inclusion of visualization improves confidence over a structured text-based input that could theoretically be helpful for answering the question. On the other hand, we observe that […]
Benchmarking the Thinking Mode of Multimodal Large Language Models in Clinical Tasks
arXiv:2511.03328v1 Announce Type: cross Abstract: A recent advancement in Multimodal Large Language Models (MLLMs) research is the emergence of “reasoning MLLMs” that offer explicit control over their internal thinking processes (normally referred as the “thinking mode”) alongside the standard “non-thinking mode”. This capability allows these models to engage in a step-by-step process of internal deliberation […]