Identifying and Reporting Child abuse

A Multimodal Fusion Model of Radiomics and Deep Learning Integrating the Tumor Microenvironment Accurately Predicts Pathological Complete Response in Breast Cancer.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is a critical prognostic marker in breast cancer, yet its prediction remains challenging due to tumor heterogeneity and limitations of conventional imaging. While radiomics and deep learning (DL) have shown promise, prior studies often neglect the peritumoral microenvironment, a key determinant of therapeutic respon...

Maximizing impact of explainable artificial intelligence in radiotherapy: a critical review.

Objective.Artificial intelligence (AI) can enable automation, improve treatment accuracy, allow for a more efficient workflow, and improve the cost-effectiveness of radiotherapy (RT). To implement AI in RT, clinicians have expressed a desire to understand the AI outputs. Explainable AI (XAI) methods have been put forward as a solution, but the multidisciplinary nature of RT complicates the applica...

Improved prediction of heavy metal concentration in typical agricultural soil in Hainan by Machine Learning method.

As machine learning (ML) techniques continue to evolve, researchers are becoming more dedicated to applying these methods to model and predict heavy m...

[Clinical Implementation of Artificial Intelligence in Endoscopy: A Human-Artificial Intelligence Interaction Perspective].

Artificial intelligence (AI) for gastrointestinal endoscopy has shown remarkable performance in detecting and characterizing lesions. A randomized con...

Enhancing kcat prediction through residue-aware attention mechanism and pre-trained representations.

The turnover number (kcat) is a key parameter in enzyme kinetics that quantifies catalytic efficiency and underpins mechanistic understanding of enzym...

Quantum-enhanced throughput pathways: Integrating Rodgers' TPM with quantum ethical frameworks for AI-driven cybersecurity.

This integrative conceptual review synthesizes psychological, ethical, and quantum-information perspectives to advance Quantum-Enhanced Throughput Mod...

Data-driven prediction of child neglect and abuse using integrated municipal sources.

BACKGROUND: Child neglect and abuse are prevalent worldwide yet often incompletely reported and are frequently associated with long-term adverse physi...

SupReMix: Supervised contrastive learning for medical imaging regression with mixup.

In medical image analysis, regression plays a critical role in computer-aided diagnosis. It enables quantitative measurements such as age prediction f...

The best from both disciplines: integrating human and microbial signatures from whole genome sequencing to advance cancer diagnostics.

Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current ap...

ELAI-SGCN: An explainable lightweight adaptive information-perceiving spiking graph convolutional network for EEG-based emotion recognition.

BACKGROUND: Emotion recognition is increasingly essential for diagnosing mental disorders like depression and anxiety. Electroencephalography (EEG) is...

Full-spectrum prompt tuning with sparse MoE for open-set recognition.

Recent advances in open-set recognition leveraging vision-language models (VLMs) predominantly focus on improving textual prompts by exploiting (high-...

Central similarity joint-learning for cross-domain retrieval.

Cross-domain retrieval holds significant research value in the field of image retrieval. However, existing cross-domain retrieval methods have the fol...

Interactive image-to-video transfer learning.

Transfer learning from image to video has become a widely adopted strategy in action recognition. Existing mainstream approaches typically fine-tune t...

IMF-DDI: Information Mapping and Fusion Framework for Drug-drug Interaction Prediction.

Drug-drug interactions (DDIs) are crucial throughout various stages of drug development. Using computer-aided methods for accurate prediction of DDIs ...

Identification of early bruising degrees in blueberries using visible and near-infrared spectroscopy coupled with deep learning.

The early detections of internal bruises in blueberries caused by external impacts after harvest play a crucial role in enhancing their economics. The...

MEGE: A mixed emotion graph model for empathetic dialogue generation.

In daily life, emotions tend to exhibit amalgamated forms. For instance, when someone is involved in an interview, excitement and nervousness consiste...

Proxy-AN loss for deep metric learning.

In deep metric learning, proxy-based losses aim to introduce proxy representations to approximate class distributions, reducing training complexity an...

Dynamic routing towards few-shot point cloud semantic segmentation.

Current 3D point-cloud semantic segmentation employs few-shot learning to lessen reliance on large-scale data. Previous prototype-based methods typica...

Remote sensing object detection through hierarchical feature mining and multivariate head collaboration with knowledge distillation.

Knowledge distillation (KD) is a proven technique for enhancing the performance of lightweight models in intelligent edge applications for remote sens...

MDSFD-Net: Alzheimer's disease diagnosis with missing modality via disentanglement learning and feature distillation.

Multi-modal analysis can provide complementary information and significantly aid in the early diagnosis and intervention of Alzheimer's Disease (AD). ...