Identifying and Reporting Child abuse

An LLM-based hybrid approach for enhanced automated essay scoring.

Automated Essay Scoring systems have traditionally relied on shallow lexical data, such as word frequency and sentence length, to assess essays. However, these approaches neglect crucial factors like text structure and semantics, resulting in limited evaluations of coherence and quality. To address these limitations, we propose a hybrid approach to AES that combines multiple features from differen...

DNA Molecular Computing with Weighted Signal Amplification for Cancer miRNA Biomarker Diagnostics.

The expression levels of microRNAs (miRNAs) are strongly linked to cancer progression, making them promising biomarkers for cancer detection. Enzyme-free signal amplification DNA circuits have facilitated the detection of low-abundance miRNAs. However, these methods may neglect the diagnostic value (or weight) of different miRNAs. Here, a molecular computing approach with weighted signal amplifica...

Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike tr...

A malware classification method based on directed API call relationships.

In response to the growing complexity of network threats, researchers are increasingly turning to machine learning and deep learning techniques to dev...

scMDCL: A Deep Collaborative Contrastive Learning Framework for Matched Single-Cell Multiomics Data Clustering.

Single-cell multiomics clustering integrates multiple omics data to analyze cellular heterogeneity and is crucial for uncovering complex biological pr...

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted a...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segmentation of brain tumors. The main objective is to ...

EMBANet: A flexible efficient multi-branch attention network.

Recent advances in the design of convolutional neural networks have shown that performance can be enhanced by improving the ability to represent multi...

Spatial heterogeneity effect of built environment on traffic safety using geographically weighted atrous convolutions neural network.

The built environment exerts a significant influence on the frequency and severity of traffic accidents. Spatially uniform assumptions on the impacts ...

FLANet: A multiscale temporal convolution and spatial-spectral attention network for EEG artifact removal with adversarial training.

Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous concern in neurophysiological signal processing, parti...

Deep learning powered single-cell clustering framework with enhanced accuracy and stability.

Single-cell RNA sequencing (scRNA-seq) has revolutionized the field of cellular diversity research. Unsupervised clustering, a key technique in this e...

Pan-sharpening via Symmetric Multi-Scale Correction-Enhancement Transformers.

Pan-sharpening is a widely employed technique for enhancing the quality and accuracy of remote sensing images, particularly in high-resolution image d...

Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.

BACKGROUND: Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structur...

UNAGI: Unified neighbor-aware graph neural network for multi-view clustering.

Multi-view graph refining-based clustering (MGRC) methods aim to facilitate the clustering of data via Graph Neural Networks (GNNs) by learning optima...

Contrastive independent subspace analysis network for multi-view spatial information extraction.

Multi-view classification integrates features from different views to optimize classification performance. Most of the existing works typically utiliz...

A universal strategy for smoothing deceleration in deep graph neural networks.

Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness ...

Unsupervised Domain Adaptation for EM Image Denoising With Invertible Networks.

Electron microscopy (EM) image denoising is critical for visualization and subsequent analysis. Despite the remarkable achievements of deep learning-b...

Counterfactual learning for higher-order relation prediction in heterogeneous information networks.

Heterogeneous Information Networks (HINs) play a crucial role in modeling complex social systems, where predicting missing links/relations is a signif...

Learning soft tissue deformation from incremental simulations.

BACKGROUND: Surgical planning for orthognathic procedures demands swift and accurate biomechanical modeling of facial soft tissues. Efficient simulati...

Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.

Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing i...