Artificial Intelligence Medical Compendium

The accurate identification and classification of medicinal plants are crucial for botanical research, pharmacology, and traditional medicine, where wrong identification or categorization of the plant species may lead to worse medical effects. In thi... read more 

Behavioral changes in animals and humans, triggered by errors or verbal instructions, can occur extremely rapidly. While learning theories typically attribute improvements in performance to synaptic plasticity, recent findings suggest that such fast ... read more 

The need for comprehensive equine welfare assessments has become particularly evident amid ongoing debates about the social licence to operate in equestrian sports. During exercise, multiple physiological systems, principally the cardiovascular, resp... read more 

OBJECTIVE: Develop a causal machine learning (causal ML) framework for estimating how a diagnosis (cancer in this study) affects the likelihood of receiving a specific health care service (advance care planning in this study) and associated heterogen... read more 

PURPOSE: Tebentafusp has emerged as the first systemic therapy to significantly prolong survival in treatment-naïve HLA-A*02:01 + patients with unresectable or metastatic uveal melanoma (mUM). Notably, a survival benefit has been observed even in the... read more 

Esophageal cancer (EC) is one of the most serious health issues around the world, ranking seventh among the most lethal types of cancer and eleventh among the most common types of cancer worldwide. Traditional therapies-such as surgery, chemotherapy,... read more 

Developing high-performance wearable flexible sensors that can adapt well to complex environments has become a hotspot. Herein, a polyvinyl alcohol based composite hydrogel sensor with high mechanical strength, desirable frost/swelling resistance, an... read more 

Laser-induced breakdown spectroscopy (LIBS) has garnered significant attention in fields such as materials science and environmental monitoring, owing to its rapid, non-destructive, and multi-element detection capabilities. However, the widespread ad... read more 

This study investigated whether unique spectral features from tracer compounds could be reliably detected and discriminated from the complex spectral background of biomaterial matrix. Spectroscopy combined with chemical markers present a promising so... read more 

The performance of graph convolutional networks (GCNs) with naive aggregation functions on nodes has reached the bottleneck, rendering a gap between practice and theoretical expressity. Some learning-based aggregation strategies have been proposed to... read more