Cultural Competence

Using Generative Artificial Intelligence in Health Economics and Outcomes Research: A Primer on Techniques and Breakthroughs.

The emergence of generative artificial intelligence (GenAI) offers the potential to enhance health e...

Prompt architecture induces methodological artifacts in large language models.

We examine how the seemingly arbitrary way a prompt is posed, which we term "prompt architecture," i...

Spanish to Mexican Sign Language glosses corpus for natural language processing tasks.

This work shares a dataset that contains Spanish (SPA) to Mexican Sign Language (MSL) glosses -trans...

The QDπ dataset, training data for drug-like molecules and biopolymer fragments and their interactions.

The development of universal machine learning potentials (MLP) for small organic and drug-like molec...

Evaluating and mitigating bias in AI-based medical text generation.

Artificial intelligence (AI) systems, particularly those based on deep learning models, have increas...

The intelligent development and preservation of folk sports culture under artificial intelligence.

To promote the intelligent development and preservation of folk sports culture, this work proposes a...

Sensitivity of a deep-learning-based breast cancer risk prediction model.

When it comes to the implementation of deep-learning based breast cancer risk (BCR) prediction model...

Delayed flowering phenology of red-flowering plants in response to hummingbird migration.

The radiation of angiosperms is marked by a phenomenal diversity of floral size, shape, color, scent...

Modified tree-based selection in hierarchical mixed-effect models with trees: A simulation study and real-data application.

Hierarchical mixed-effects models with three trees-3Trees models-are a new advanced statistical lear...

High-order diversity feature learning for pedestrian attribute recognition.

Pedestrian attribute recognition (PAR) involves accurately identifying multiple attributes present i...

Detecting implicit biases of large language models with Bayesian hypothesis testing.

Despite the remarkable performance of large language models (LLMs), such as generative pre-trained T...

Using fuzzy decision support to create a positive mental health environment for preschoolers.

The preschool period is a crucial time for behavioural and social-emotional development and the cult...

Compact CNN module balancing between feature diversity and redundancy.

Feature diversity and redundancy play a crucial role in enhancing a model's performance, although th...

AI-enhanced resuscitation image production training: advancing diversity and inclusion with GPT-4o.

Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study.

BACKGROUND: Manual landmark detection in cone beam computed tomography (CBCT) for evaluating craniof...

Novel AI applications in systematic review: GPT-4 assisted data extraction, analysis, review of bias.

OBJECTIVE: To assess custom GPT-4 performance in extracting and evaluating data from medical literat...

Prompting large language models to extract chemical‒disease relation precisely and comprehensively at the document level: an evaluation study.

Given the scarcity of annotated data, current deep learning methods face challenges in the field of ...

NA_mCNN: Classification of Sodium Transporters in Membrane Proteins by Integrating Multi-Window Deep Learning and ProtTrans for Their Therapeutic Potential.

Sodium transporters maintain cellular homeostasis by transporting ions, minerals, and nutrients acro...

Boosting semi-supervised federated learning by effectively exploiting server-side knowledge and client-side unconfident samples.

Semi-supervised federated learning (SSFL) has emerged as a promising paradigm to reduce the need for...

The Emergence of AI in Public Health Is Calling for Operational Ethics to Foster Responsible Uses.

This paper discusses the responsible use of artificial intelligence (AI) in public health and in med...

Localize-diffusion based dual-branch anomaly detection.

Due to the scarcity of real anomaly samples for use in anomaly detection studies, data augmentation ...