Artificial Intelligence Medical Compendium

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BACKGROUND: Drug screening constitutes the predominant paradigm for novel drug discovery. With the development of omics, drug screening has gradually developed into pharmacotranscriptomics-based drug screening (PTDS), which is different from target-b... read more 

α-Quartz () surfaces functionalized with hydroxyl () and methyl () groups provide a versatile platform for controlling interfacial properties critical to applications such as catalysis, protective coatings, and energy conversion. The arrangement of t... read more 

Community Value Prediction (CVP) is an important emerging task in the field of social commerce, which aims to predict the community values. However, due to the complex structure of communities and individuals, previous graph machine learning methods ... read more 

Large-scale probabilistic Boolean networks (LSPBNs) are a modeling tool used to simulate and analyze the dynamics of complex systems with uncertainty. However, due to its high computational complexity, previous research methods cannot be directly app... read more 

Accurate detection of 5-hydroxytryptamine (5-HT) is essential for the diagnosis and treatment of clinical depression. A functionalized film was fabricated by electropolymerizing graphene oxide (GO) and l-arginine (L-Arg) hybrid onto the electrode sur... read more 

Image restoration aims to recover high-quality images from their degraded counterparts, necessitating a delicate balance between preserving spatial details and capturing contextual information. Although some methods attempt to address this trade-off,... read more 

Radiology report generation, which aims to provide accurate descriptions of both normal and abnormal regions, has been attracting growing research attention. Recently, despite considerable progress, data-driven deep-learning based models still face c... read more 

Terahertz time-domain spectroscopy (THz-TDS) stands out as a prominent spectroscopic technique ideal for identifying explosives. The integration of THz data with machine learning models enables rapid identification and classification of explosive mol... read more 

Heterogeneous Graph Neural Networks (HGNNs) are advanced deep learning methods widely applied for learning representations of heterogeneous graphs. However, they face challenges such as over-smoothing and non-robustness. Existing methods can mitigate... read more