Machine learning algorithms are the core of machine learning systems. These algorithms are designed to learn from data and make predictions or decisions without being explicitly programmed to perform ...

To develop a context-aware multi-instance learning (TransMIL) model based on whole-slide pathological images and integrate it with clinical parameters, thereby constructing a multimodal model for ...

Abstract: The growing scale of modern transmission networks poses significant challenges for effective and intuitive visualization and analysis. By partitioning networks by voltage level, a ...

The Precedence Diagram Method (PDM) is widely used for modeling large and complex construction projects characterized by non-linear execution logic, overlapping activities, and multiple precedence ...

Global consumption of artificial sweeteners (ASs) has risen substantially in recent years. However, their relationship with prostate cancer (PCa) remains poorly characterized. This study investigates ...

Abstract: The verbose responses generated by Large Language Models during multi-turn interactions substantially impair reading efficiency, while their limited short-term memory mechanisms hinder users ...

This project provides a generic (Java FX) graph visualization library that can automatically arrange the vertices' locations through a force-directed algorithm in real-time. Since the visualization is ...

Geometric and Multi-Scale Feature Fusion for Complete Tree Skeleton Extraction. The point cloud data obtained by 3D reconstruction of the tree body is missing, which exacerbates the problem of missing ...

Cholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore ...