AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. HER2-targeted therapies have improved outcomes for HER2-positive patients, highlighting the importance of accurate as...
UNLABELLED: Childhood obesity is the main driver of early metabolic risk, predisposing to cardiovascular disease (CVD) and type 2 diabetes (T2D), which cause millions of deaths worldwide. Their progression is influenced by biological, behavioral, and...
BACKGROUND: The evolution of language models, particularly large language models, has introduced transformative potential for psychological assessment, challenging traditional rating scale methods that have dominated clinical practice for over a cent...
Medical oncology (Northwood, London, England)
Jan 13, 2026
Recent advances in Medical Oncology highlight the integration of bulk and single-cell transcriptomics to reveal glycolytic heterogeneity in colorectal cancer. Translating these discoveries into reliable clinical tools requires rigorous methods, trans...
When given a sample of 100 emergency department discharge instructions, Claude Sonnet, a large language model, produced accurate Spanish translations as evaluated by Spanish-speaking physicians and medical interpreters.
Recent advances in artificial intelligence (AI) and machine learning (ML) are revolutionizing nanopharmaceutical development by enabling data-driven formulation design, process optimization, and prediction of biological performance. AI encompasses co...
BACKGROUND: Digital wound monitoring has become increasingly feasible with the widespread use of smartphones and mobile messaging platforms. Although most previous studies have focused on chronic wounds and demonstrated the clinical benefits of remot...
BACKGROUND: High-quality clinical chains-of-thought (CoTs) are essential for explainable medical artificial intelligence (AI); yet, their development is limited by data scarcity. Large language models can generate medical CoTs, but their clinical rel...
BACKGROUND: Undiagnosed cognitive impairment poses a global challenge, prompting recent interest in ultra-brief screening questionnaires (comprising <2 to 3 items) to efficiently identify individuals needing further evaluation. However, evidence on u...
This paper proposes a hybrid ensemble classifier with denoising autoencoder (ECDAE) framework to address reliability and robustness challenges in cooperative spectrum sensing (CSS) for cognitive radio networks (CRNs). The proposed framework first emp...
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