Pneumonia

Community Characteristics Predict Local News Agenda Building About Racial Health Disparities.

We examined market-level social and demographic characteristics and station-level factors as predictors of local television news coverage of COVID-19-related racial disparities using the theoretical lens of agenda building and the community structure theory. We analyzed closed captioning of evening news broadcasts from 758 stations tracked in all 210 media markets from February 1 2020, to November...

Explainable artificial intelligence-enabled intertwined logistics analytics with application in poultry vaccine distribution in the Northwest of Iran.

Intertwining supply chains integrates the corresponding networks across several intersection points, such as suppliers, manufacturers, and transporters, resulting in higher viability and efficiency. Nonetheless, no formulation has been proposed for intertwined logistics planning. In addition, interpretable machine learning models, such as multiple linear regression models, may not be an accurate m...

Chest X-Ray evaluation using GPT for tube thoracostomy or conservative care in non-tension spontaneous pneumothorax.

BACKGROUND/OBJECTIVE: Spontaneous pneumothorax (SP) commonly presents to the emergency department (ED), and clinicians must rapidly decide between con...

Development and validation of the Oxford Attitudes to Artificial Intelligence in Medicine Scale.

OBJECTIVE: Public willingness to accept medical artificial intelligence (AI) tools affect the potential real-world impact of these evolving technologi...

Tuberculosis Disease Severity Assessment Using Clinical Variables and Radiology Enabled by Artificial Intelligence.

BACKGROUND: Chest X-ray (CXR) can assess pulmonary tuberculosis (TB) severity and may guide duration of treatment. However, the optimal radiological m...

Serum mass spectral fingerprints with machine learning for early discrimination of infectious pneumonia in the emergency department.

Generative artificial intelligence-driven chatbots and medical misinformation: an accuracy, referencing and readability audit.

OBJECTIVES: Artificial intelligence (AI)-driven chatbots have been rapidly adopted across research, education, business, marketing and medicine. Most ...

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community.

BACKGROUND: Breast cancer affects millions of women and presents not only medical challenges but also emotional, financial, and social burdens. Beyond...

Personalized Digital Care Program Allocation for Older Adults: Reinforcement Learning-Based Simulation Study.

BACKGROUND: As the demand for innovative older adult care grows alongside a shortage of care workers, personalization is key to optimizing services an...

Enhancing Recommendation Systems through SVD-based collaborative filtering and community detection.

The recommendation systems often face challenges like low data density, scalability issues and absence of interpretability, whereas classical Collabor...

Personalized neoantigen cancer vaccines: Why clinical benefit remains inconsistent.

Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen id...

Serum-free media for cultivated meat: from cellular mechanisms to cost-effective bioprocess design.

Serum-free media (SFM) determine whether cultivated meat (CM) can progress from pilot studies to scalable, food-grade manufacturing. Replacing fetal b...

Integrating metagenomics into legume breeding: A breeder-centered roadmap from core microbiomes to precision inoculation.

Metagenomics, culture-independent profiling of genetic material recovered from environmental samples, provides a powerful route to characterize microb...

MIFE and MIFD: Minimum information for fermentation experiments and devices.

BACKGROUND: As the technological advancements of the early 21st century are pushing industrial biotechnology (IB) into the realm of Big Data driven in...

Raising Awareness in the Nursing Community About 'Tortured Phrases'.

The academic nursing community across Canada and worldwide relies on literature with technically accurate terms. Despite this, scientific literature c...

S3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network.

Convolutional Neural Networks (CNNs) have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial fea...

Efficient SqueezeViT: A lightweight vision transformer framework for chest X-ray image classification.

This work introduces SqueezeViT (Squeeze Vision Transformers), a compact yet effective architecture based on Vision Transformers (ViT) designed for ch...

K-STAMM: a knowledge-enhanced spatial - temporal attention model with multimodal fusion for pneumonia prediction.

Precise prediction of pneumonia remains a challenge mainly because effective integration of clinical data that are highly heterogeneous is mandatory. ...

Clinical evaluation of an AI-based pneumonia detection system on chest CT: a qualitative and quantitative analysis.

Integrated approach for arsenic prediction and health risk evaluation in community tube wells installed by public health department: comparative study of random forest, extreme gradient boosting, and deep neural networks.

Arsenic contamination in groundwater poses a significant public health risk, especially in developing countries with inadequate water quality monitori...