Artificial Intelligence Medical Compendium

Recent advances in open-set recognition leveraging vision-language models (VLMs) predominantly focus on improving textual prompts by exploiting (high-level) visual features from the final layer of the VLM image-encoder. While these approaches demonst... read more 

Novel multifunctional packaging for monitoring and maintaining food freshness has been developed. Bilayer films based on polysaccharides incorporating red cabbage anthocyanins were prepared. Anthocyanins were encapsulated in the inner layer based on ... read more 

BACKGROUND: Gait disturbance is a core feature of Parkinson's disease (PD), contributing to mobility loss and fall risk. Rhythmic auditory stimulation (RAS) can improve gait, yet response varies across patients. This study evaluated RAS effects on ga... read more 

Gender equity in academic veterinary science remains underexplored outside of Western countries. This study aimed to evaluate gender representation across academic ranks within veterinary institutions in Asia, Sub-Saharan Africa, Latin America, and t... read more 

Atractylodis Macrocephalae Rhizoma (AMR) is classified as a medicinal and edible homologous food in China. Based on the fusion of multi-source information, this study comprehensively reveals the changing patterns of appearance, texture and compositio... read more 

This study establishes an integrative machine learning (ML) framework that bridges environmental psychology and data science to investigate the psychological well-being of older adults in urban green spaces (UGS). We applied decision tree (DT), rando... read more 

Accurate classification of aluminum alloys with minor compositional differences remains a challenge for laser-induced breakdown spectroscopy (LIBS) due to spectral similarity and matrix effects. Herein, we propose a time-frequency dual-domain enhance... read more 

BACKGROUND AND OBJECTIVES: Despite the significant potential of Foundation Models (FMs) in medical imaging, their application to prognosis prediction remains challenging due to data scarcity, class imbalance, and task complexity, limiting their clini... read more 

Deep-learning (DL) algorithms are widely promoted for diabetic-retinopathy (DR) screening, yet their prospective diagnostic accuracy is not well defined. PubMed, EMBASE and ClinicalTrials.gov were searched to April, 2025, for prospective evaluations ... read more 

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