Artificial Intelligence Medical Compendium

In fully cooperative environments, agents aim to learn a joint policy to achieve a shared goal. However, existing Multi-Agent Reinforcement Learning (MARL) approaches struggle when scaling to complex coordination tasks. However, as the complexity of ... read more 

With the development of digital imaging in medical microscopy, artificial intelligent-based analysis of pathological whole slide images (WSIs) provides a powerful tool for cancer diagnosis. Limited by the expensive cost of pixel-level annotation, cur... read more 

BACKGROUND AND OBJECTIVE: Patient-ventilator asynchrony (PVA) is prevalent in mechanically ventilated patients and adversely impacts clinical outcomes, but its real-time detection remains challenging. While artificial intelligence (AI) systems show p... read more 

In the context of global warming, understanding the evolving patterns of extreme snowfall is a critical scientific challenge. This study investigates the spatiotemporal trends, atmospheric drivers, and thermodynamic mechanisms of snowfall in China fr... read more 

Major depressive disorder (MDD) and Hashimoto's thyroiditis (HT) frequently co-occur, yet their shared molecular underpinnings remain unclear. We performed an integrative transcriptomics analysis combining transcriptomic profiling, immune cell deconv... read more 

Gamma oscillations are critical for cortical cognitive processing. The ability to generate gamma oscillations evolves with age and requires cellular adjustments of the underlying neural networks. In the prefrontal cortex, gamma oscillations emerge re... read more 

Graph Neural Networks (GNNs) are the most common approach for learning complex relational data represented using graph data structures. Although GNNs are effective at learning representations of both nodes and graphs for a given task, the learning pr... read more 

Knowledge distillation (KD) using machine translation (MT) teacher models has demonstrated effectiveness in enhancing end-to-end speech-to-text translation (ST). However, existing KD methods for ST primarily rely on the teacher's output distributions... read more 

Recognizing the structure of tabular (image) data aims to convert the table on the image to a machine-readable representation. The structure of tabular data is complex and diverse, including cases such as cell spanning, nested cell spanning, cell vac... read more 

Flexible modulation of temporal dynamics in neural sequences underlies many cognitive processes. For instance, we can adaptively change the speed of motor sequences and speech. While such flexibility is influenced by various factors such as attention... read more