INTRODUCTION: Community health workers (CHWs) are critical to healthcare delivery in low-resource settings but often lack formal clinical training, limiting their decision-making. Large language models (LLMs) could provide real-time, context-specific...
INTRODUCTION: Mother-infant skin-to-skin contact (SSC) improves developmental and cognitive outcomes in preterm infants. However, the effects of SSC on healthy term infants remain unclear. We aim to investigate the short-term and long-term impacts of...
BACKGROUND: Trauma exposure is highly prevalent and associated with various health issues. However, health care professionals can exhibit trauma-related diagnostic overshadowing bias, leading to misdiagnosis and inadequate treatment of trauma-exposed...
BACKGROUND: Amidst the COVID-19 pandemic, the proliferation of misinformation on social media, termed the "infodemic," has complicated global health responses.
BACKGROUND: Large language model (LLM)-based artificial intelligence (AI) coaches show promise for personalized exercise and health interventions. However, the unique demands of ensuring safety and real-time, multimodal personalized feedback have cre...
BACKGROUND: Emoji are a universal visual language widely used in digital communication; yet, their representation of medical concepts remains limited. The introduction of medical emojis, such as the anatomical heart and lungs, highlights their potent...
BACKGROUND: Disappointing medical care (DMC) encompasses cases of medical failures, malpractice, or errors. Literature suggests that individuals' perceptions of harm resulting from medical procedures influence their intention to seek legal recourse a...
Accurate detection of brain midline shift is critical for the diagnosis and monitoring of neurological conditions such as traumatic brain injuries, strokes, and tumors. This study aims to address the lack of dedicated datasets and tools for this task...
This study aims to offer a multilayered assessment of the adoption and implementation of robotic surgery (RS) in Türkiye by centring surgeons' individual experiences while concurrently examining institutional conditions and broader health-system fact...
Gastric cancer (GC) is a highly heterogeneous disease that requires highly accurate prognostic models. Machine learning is a powerful tool for identifying predictive biomarkers and developing prognostic models. Here, we aim to integrate bioinformatic...
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