Cultural Competence

Big Data in Neurosurgery: A Guideline on Data Structures, Machine Learning Models, and Ethical Considerations.

Artificial intelligence (AI) is reshaping neurosurgery, offering unprecedented opportunities to enhance diagnostics, personalize treatment, and predict outcomes. At the heart of this transformation is the ability to effectively harness big data (BD) within the electronic medical record. Understanding these data structures is essential for making sense of the vast volumes of information generated i...

Are Artificial Intelligence Models Reliable for Clinical Application in Pediatric Fracture Detection on Radiographs? A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence (AI) applications for pediatric fracture diagnosis using radiographs have demonstrated growing potential in clinical settings. Despite this growing potential, existing studies are limited by small sample sizes, variability in their diagnostic metrics, and inconsistent use of external validation, which reduces confidence in their findings. These limitations hinde...

Machine Learning-Aided Meta-Analysis Reveals Changes in Penaeus vannamei Gut Bacterial Communities Upon Dietary Supplementation-Induced Immunostimulation.

Gut bacterial communities play a key role in shrimp health; thus, their modulation has been a target of dietary supplements which also function in enh...

Portrayal of Cancer Patients in the Era of AI: A Content Analysis of Images Produced by Generative AI Tools.

This study sought to characterize images of cancer patients generated by Artificial Intelligence (AI) text-to-image tools, and assess whether images d...

Global genomics of Lactococcus lactis: horizontal gene transfer and intergenic variation drive multiple domestication and dairy adaptation.

INTRODUCTION: Lactococcus lactis is a crucial lactic acid bacterium of great economically significance for cheese product. The species exhibits wildly...

The 2024 Declaration of Helsinki Revision: Relevance to Nursing Research.

BACKGROUND: The 2024 revision of the Declaration of Helsinki (DoH) marks a pivotal shift in biomedical research ethics, with significant implications ...

Predicting the First Onset of Suicidal Thoughts and Behaviors in Adolescents Using Multimodal Risk Factors: A 4-Year Longitudinal Study.

OBJECTIVE: Suicide is one of the leading causes of death among youth worldwide, yet existing studies that aimed to predict the first onset of suicidal...

Advancing fungal phylogenetics: integrating modern sequencing, dark taxa discovery, and machine learning.

The study of fungal genetics has undergone transformative advancements in recent decades, profoundly reshaping our understanding of fungal diversity, ...

Neural correlates of evaluative bias against AI-labeled versus human-labeled artworks.

The rapid advancement of generative artificial intelligence (AI) has enabled machines to produce creative outputs, such as artworks, that rival human ...

A Study of Data Augmentation for Learning-Driven Scientific Visualization.

The success of deep learning heavily relies on the large amount of training samples. However, in scientific visualization, due to the high computation...

Asymptotic theory of in-context learning by linear attention.

Transformers have a remarkable ability to learn and execute tasks based on examples provided within the input itself, without explicit prior training....

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technolog...

Machine Learning Identifies Sexual Behavior Subgroups Among Men Who Have Sex with Men in Switzerland.

Sexual behavior is heterogeneous and dynamic. Characterization of such complexity constitutes evidence for public health authorities and caregivers co...

Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.

Trait Genome-to-Phenome (G2P) dimensionality and "breeding context" combine to influence the realised prediction skill of different whole genome predi...

Utility of synthetic musculoskeletal gaits for generalizable healthcare applications.

Deep-neural-network-based artificial intelligence enables quantitative gait analysis with commodity sensors. However, current gait-analysis models are...

Assessing risk of bias in toxicological studies in the era of artificial intelligence.

Risk of bias is a critical factor influencing the reliability and validity of toxicological studies, impacting evidence synthesis and decision-making ...

Multidimensional surface-enhanced Raman scattering biosensor integrated convolutional neural networks for accurate bacteria identification.

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful technique for bacterial detection, offering high sensitivity and molecular-level ...

Demystifying the Dermatology Residency Application Process, Part II - Application Season: Strategic Application, Interviewing, and Mentorship.

The dermatology residency match has become increasingly competitive, culminating in a 2025 United States senior MD match rate of 63 % according to the...

Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications.

Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive ...

Associations between weight gain, integrase inhibitors antiretroviral agents, and gut microbiome in people living with HIV: a cross-sectional study.

Dolutegravir and bictegravir are second-generation HIV integrase strand transfer inhibitors (INSTIs) that were previously associated with abnormal wei...