Artificial Intelligence Medical Compendium

Residual quinolone antibiotics (lomefloxacin [LOM], ofloxacin [OFL], pefloxacin [PEF]) in food matrices present significant public health risks due to bioaccumulation and toxicity, necessitating field-deployable methods with superior sensitivity over... read more 

Proteins and peptides from functional foods offer notable health benefits, yet their efficacy is hindered by low solubility, enzymatic degradation, poor absorption, metabolic limitations, and gastrointestinal instability. This review summarizes the m... read more 

Type 2 diabetes mellitus (T2DM) is a global disease threatening human health. Regulating blood glucose homeostasis is a key strategy for the treatment of T2DM. In recent years, animal skin-derived hypoglycemic peptides (ASHP) have been proven to effe... read more 

The geographical origin of raw materials critically influences the polyphenol (PPs) profile of plant-derived products (PDPs), which in turn determines their quality and authenticity. Herein, we report a smartphone app-enabled dual-mode (colorimetric/... read more 

BACKGROUND: Baseline lung allograft dysfunction (BLAD), defined as failure to achieve ≥ 80% predicted spirometry after lung transplant, is associated with reduced survival. This study aimed to determine the prevalence and character of computed tomogr... read more 

Developmental dysplasia of the hip (DDH) causes preventable morbidity when diagnosis is delayed. We review advances that address screening gaps: 3-dimensional (3D) ultrasound for volumetric visualization with retrospective plane selection; artificial... read more 

With the increasing Alzheimer's disease (AD) prevalence, morbidity, and mortality, its early diagnosis is particularly important. The multi-modal data can be used to analyze intermodal feature relationships and enhance the feature expression ability ... read more 

Multispectral remote sensing object detection plays a vital role in a wide range of geoscience and remote sensing applications, such as environmental monitoring and disaster monitoring, by leveraging complementary information from RGB and infrared mo... read more 

BACKGROUND: Prognosis prediction for high-risk patients undergoing invasive coronary angiography (ICA) is crucial for clinical decision-making. Despite machine learning (ML) advancements, time-to-event survival prediction remains limited. OBJECTIVES:... read more 

The diagnosis and identification of mental disorders are widely recognized as a global challenge. The emergence of Graph Neural Networks (GNNs) has significantly advanced brain network analysis. However, the heterogeneity and scarcity of medical imag... read more