BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery...
Although general-purpose artificial intelligence (GPAI) is widely expected to accelerate scientific discovery, its practical limits in biomedicine remain unclear. We assess this potential by developing a framework of GPAI capabilities across the biom...
BACKGROUND: The integration of artificial intelligence (AI) and machine learning (ML) into biomedical research requires a workforce fluent in both computational methods and clinical applications. Structured, interdisciplinary training opportunities r...
Rectal cancer presents complex surgical challenges due to the confined pelvic anatomy. Robotic-assisted surgery has gained prominence for its enhanced precision, dexterity, and ergonomics compared to conventional laparoscopy. This bibliometric analys...
BACKGROUND: The accurate extraction of biomedical entities in scientific articles is essential for effective metadata annotation of research datasets, ensuring data findability, accessibility, interoperability, and reusability in collaborative resear...
BACKGROUND: Over 300 million individuals worldwide live with Atopic Dermatitis and Psoriasis, which are among the most common chronic inflammatory skin diseases. Multimodal biomarkers are currently being developed using large-scale data and artificia...
BACKGROUND: Traditional, complementary, and integrative (TCI) medicine is an essential component of health systems worldwide, especially in low- and middle-income countries. Despite its widespread use, existing research on the safety, efficacy, and i...
BACKGROUND: Inflammatory bowel disease (IBD) research is a dynamic field. However, the growing volume of electronic health records (EHRs) and research data presents significant challenges. Traditional methods for structuring unstructured EHRs are lab...
As machine learning (ML) becomes increasingly central to biomedical research, the need for trustworthy models is more pressing than ever. In this paper, we present nine concise and actionable tips to help researchers build ML systems that are technic...
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