Latest AI and machine learning research in cultural competence for healthcare professionals.
Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs) like GPT-4 offer a potential tool for personalizing health communication, but their ability to correct gender gaps without introducing new biases is unknown. We identified seven publicly available English-language CVD prevention handouts from major ...
Systematic reviews (SRs) are essential for evidence-based practice but remain labor-intensive, especially during abstract screening. This study evaluates whether multiple large language model (multi-LLM) collaboration can improve the efficiency and reduce costs for abstract screening. Abstract screening was framed as a question-answering (QA) task using cost-effective LLMs. Three multi-LLM collabo...
The proliferation of food delivery applications has fundamentally transformed urban dietary behaviors, creating unprecedented shifts in meal consumpti...
Electronic health record (EHR) data often missed care outside a given health system, resulting in data discontinuity. We aimed to: (1) quantify miscla...
To develop and evaluate an automatic patient review analyzer that applies advanced Natural Language Processing (NLP) and machine learning methods to i...
Colorectal cancer is the third leading cause of cancer-related deaths in the United States, and colonoscopy remains the gold standard for early detect...
Primary care is facing multiple crises, including an increase in health misinformation. Digital health messaging by primary care providers has been sh...
Bias in machine learning is a persistent challenge because it can create unfair outcomes, limit generalization, and reduce trust in real-world applica...
Heart failure (HF), including heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), remains...
Type 1 diabetes (T1D) is strongly influenced by HLA variation, yet current genetic risk models developed largely in European cohorts perform suboptima...
Large language models are increasingly used for clinical decision support yet may perpetuate socioeconomic biases. Whether simple prompt-based interve...
This study aimed to systematically review and critically evaluate the risk of bias and applicability of surgical site infection (SSI) risk prediction ...
The emergence of generative AI and controllable diffusion has made image-to-image synthesis increasingly practical and efficient. However, when inpu...
Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine le...
Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when intera...
Artificial intelligence (AI) systems are increasingly being integrated in clinical care, including for AI-powered note-writing. We aimed to develop an...
Malaria remains a significant global health burden, particularly in resource-limited regions where timely and accurate diagnosis is critical to effe...
Visitors to cultural heritage sites often encounter official information, while local people's unofficial stories remain invisible. To explore expre...
Introduction: Healthcare AI models often inherit biases from their training data. While efforts have primarily targeted bias in structured data, men...
The rapid development of large language models (LLMs) and large vision models (LVMs) have propelled the evolution of multi-modal AI systems, which h...