From Theory to Practice: Viewpoint on Economic Indicators for Trust in Digital Health.

User trust is pivotal for the adoption of digital health systems interventions (DHI). In response, numerous trust-building guidelines have recently emerged targeting DHIs such as artificial intelligence. The common aim of these guidelines aimed at private sector actors and government policy makers is to build trustworthy DHI.

Emerging models to study competitive interactions within bacterial communities.

Within both abiotic and host environments, bacteria typically exist as diverse, multispecies communities and have crucial roles in human health, agriculture, and industry. In these communities, bacteria compete for resources, and these competitive interactions can shape the overall population structure and community function. Studying bacterial community dynamics requires experimental model systems that capture the different interaction networks between bacteria and their surroundings.

Combined endonasal, endo-orbital and transcranial craniofacial resection of invasive anterior skullbase sinonasal carcinoma: 2D endoscopic video.

Background: Sinonasal malignancies, in which squamous cell carcinomas are the most common are rare and difficult to treat given the location and anatomical structures involved. Sinonasal malignancies often present late due to non-specific and benign symptoms. Partial resections are often associated with poorer outcomes [1].

Evaluation of Generative Artificial Intelligence Models in Predicting Pediatric Emergency Severity Index Levels.

Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.

Mapping of high-resolution daily particulate matter (PM) concentration at the city level through a machine learning-based downscaling approach.

PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km resolution needs to be revised to depict spatial variation in smaller regions accurately.