Facial plastic surgery & aesthetic medicine
Feb 5, 2026
BACKGROUND: Artificial intelligence (AI) and machine-learning technology are on the rise, including ChatGPT and Google's Gemini, previously known as Bard. While recent studies have begun to explore the role of AI in medicine, there are no studies to ... read more
BACKGROUND: Secondary distribution of HIV self-testing can expand testing among men who have sex with men. A parent quasi-experimental trial found that sexual health influencers (SHIs) identified by a machine-learning model achieved greater peer upta... read more
Introduction: Current workflows for studying hydrocephalus in rodent models rely on manual segmentation or qualitative assessment of ventricular size on small animal magnetic resonance imaging, which are both inefficient and prone to variability. Atl... read more
Aphasia, an acquired language deficit, is the most common post-stroke focal cognitive impairment, and roughly 60% cases become chronic (duration >6 months). Aphasia therapies could be optimized if clinicians could make personalized predictions of how... read more
Numerous studies have shown that the morphological phenotype of a cell or organoid correlates with its susceptibility to anti-cancer agents. However, traditional methods of measuring phenotype rely on spatial metrics such as area, volume, perimeter, ... read more
A priori model informed precision dosing (MIPD) recommends an appropriate first dose based solely on the covariates of the patient enabling faster target attainment without required concentration measurements. Population pharmacokinetic model ensembl... read more
Mass spectral molecular networking (MN) has emerged as a key computational approach to organize and analyze the vast volumes of tandem mass spectrometry (MS/MS) data generated in natural product research. MN connections are based on mass spectral sim... read more
Mitochondrial dysfunction is implicated in a wide range of disorders, including cancer, neurodegeneration, and cardiovascular diseases. Conventional assays typically assess mitochondrial function by measuring bulk respiration rates across thousands o... read more
Design-Build-Test-Learn (DBTL) cycles are a widely employed engineering framework in metabolic engineering. Nonetheless, their performance depends on a wide range of experimental and algorithmic design choices, whose combined effects on the successfu... read more
The application of Large Language Models (LLMs) for generating data visualizations through natural language interaction represents a promising advance in AI-assisted scientific analysis. However, existing LLM-based tools largely emphasize graph gener... read more
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