Artificial Intelligence Medical Compendium

BACKGROUND: Postpolypectomy surveillance intervals derived from colonoscopy findings and histopathology should be guideline-based, yet these are frequently not adhered to, contributing to under- and oversurveillance. This motivates a more structured ... read more 

Inferring gene regulatory networks (GRNs) is crucial for understanding the complex regulatory relationships that govern gene expression in cells. Recently, several computational methods have been proposed for reconstructing GRNs from single-cell RNA ... read more 

With the rapid development of deep learning, supervised convolutional neural network methods have greatly improved the performance of low-dose computed tomography (CT) denoising. However, they require paired noisy-clean training data, which is diffic... read more 

Cardiovascular disease (CVD) remains the leading cause of death worldwide. While clinical scores provide modest predictive accuracy, the electrocardiogram (ECG) is rarely leveraged for prognosis. Artificial intelligence (AI) and deep learning now ena... read more 

The deepening integration of generative AI into design education is driving a paradigm shift in human-computer AI collaboration (HAIC) -from mere tool assistance toward intelligent synergy. However, its dual impact on the competency development of de... read more 

The energy landscape picture is a central tool to study many-body systems. In particular, the energy landscapes of glass-forming liquids, jammed packings, constraint satisfaction problems, or neural networks contain a plethora of minima corresponding... read more 

As machine learning (ML) enters high-stakes domains, trustworthy uncertainty quantification (UQ) is essential for safety. In this paper we introduce PCS-UQ, a framework based on the predictability, computability, and stability (PCS) principles for ve... read more 

Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fundamental challenge across science and engineering. Traditional stability and receptivity (resolvent... read more 

Semantic segmentation of high-resolution remote sensing imagery in complex urban scenes often suffers from insufficient modeling of boundary neighborhoods, causing ambiguity near class interfaces and weakening the continuity of elongated structures. ... read more 

Artificial intelligence-generated content (AIGC) is increasingly embedded in short-video platforms, where algorithmic recommendation systems expose users to high volumes of rapidly produced synthetic media. Although prior research has examined genera... read more