BeOne Medicines has tapped former professional soccer goalkeeper Tim Howard as the face of its first major corporate campaign, which plays on how the company is geared up to “save” lives.
After refusing to resign, CDER head Høeg is fired
The turmoil at the FDA continues with the news that Tracy Beth Høeg has been fired as acting head of CDER, to be replaced by Michael Davis.
Study on the characteristics analysis and recognition method of vowels in patients with type Ⅱ diabetes
Type 2 diabetes mellitus (T2DM) can induce impairments in vocal fold function and neural control, resulting in systematic changes in vowel articulation that may serve as objective biomarkers for speech-based disease detection. Traditional sentence-level approaches are susceptible to linguistic variability, limiting their ability to extract disease-specific acoustic features and reducing overall robustness. This study presents […]
Study on the characteristics analysis and recognition method of vowels in patients with type Ⅱ diabetes
Type 2 diabetes mellitus (T2DM) can induce impairments in vocal fold function and neural control, resulting in systematic changes in vowel articulation that may serve as objective biomarkers for speech-based disease detection. Traditional sentence-level approaches are susceptible to linguistic variability, limiting their ability to extract disease-specific acoustic features and reducing overall robustness. This study presents […]
Artificial intelligence and digital health equity: a post-pandemic evidence synthesis and implementation safeguards framework
IntroductionThe rapid expansion of AI-enabled digital health after COVID-19 created new possibilities for extending care while raising concerns about unequal access, subgroup underperformance, and weak accountability. These effects remain difficult to interpret because telehealth infrastructure, predictive analytics, clinical decision support, and generative AI operate through different equity mechanisms.MethodsA transparent narrative evidence synthesis was conducted using […]
Artificial intelligence and digital health equity: a post-pandemic evidence synthesis and implementation safeguards framework
IntroductionThe rapid expansion of AI-enabled digital health after COVID-19 created new possibilities for extending care while raising concerns about unequal access, subgroup underperformance, and weak accountability. These effects remain difficult to interpret because telehealth infrastructure, predictive analytics, clinical decision support, and generative AI operate through different equity mechanisms.MethodsA transparent narrative evidence synthesis was conducted using […]
Rationale and methods of the MOVI-HIIT! cluster-randomized controlled trial: an avatar-guided virtual platform for classroom activity breaks and its impact on cognition, adiposity, and fitness in preschoolers
IntroductionClassroom-based active breaks (ABs) have been shown to reduce sedentary time and increase physical activity in primary school children; however, evidence regarding their effects on body composition, physical fitness, cognition and other health-related outcomes remains limited in preschool children. This article describes the rationale and prespecified methods of the MOVI-HIIT study, a cluster-randomised controlled trial […]
Detecting Privilege Escalation in Polyglot Microservices via Agentic Program Analysis
arXiv:2605.15569v1 Announce Type: cross Abstract: Microservices are widely adopted in modern cloud systems due to their scalability and fault tolerance. However, microservice architectures introduce significant complexity in privilege and permission control, creating risks of privilege escalation where attackers can gain unauthorized access to resources or operations. Detecting such vulnerabilities is challenging due to complex cross-service […]
Hybrid LLM-based Intelligent Framework for Robot Task Scheduling
arXiv:2605.15486v1 Announce Type: cross Abstract: This study introduces intelligent frameworks that use Large Language Models (LLMs) to improve task scheduling for construction robots. The LLM is fed with key data about the desired task, such as agent action abilities, and the desired end goal to be achieved. A well-balanced allocation strategy is developed, optimizing both […]
Process Rewards with Learned Reliability
arXiv:2605.15529v1 Announce Type: cross Abstract: Process Reward Models (PRMs) provide step-level feedback for reasoning, but current PRMs usually output only a single reward score for each step. Downstream methods must therefore treat imperfect step-level reward predictions as reliable decision signals, with no indication of when these predictions should be trusted. We propose BetaPRM, a distributional […]
MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes
arXiv:2605.15423v1 Announce Type: cross Abstract: Modern smart vision sensors need on-device intelligence to process video streams, as cloud computing is often impractical due to bandwidth, latency, and privacy constraints. However, these sensory systems typically rely on ultra-low-power microcontrollers (MCUs) with limited memory and compute, making conventional video object detection methods, which require feature storage or […]
BiomedAP: A Vision-Informed Dual-Anchor Framework with Gated Cross-Modal Fusion for Robust Medical Vision-Language Adaptation
arXiv:2605.15736v1 Announce Type: cross Abstract: Biomedical Vision–Language Models (VLMs) have shown remarkable promise in few-shot medical diagnosis but face a critical bottleneck: textitfragility to prompt variations.Existing adaptation frameworks typically optimize visual and textual prompts as independent streams, relying on ideal “Golden Prompts”. In clinical reality, where descriptions are often noisy and heterogeneous, this modality isolation […]