Identifying and Reporting Dependent Adult abuse

Artificial Intelligence in Dentistry: A Concise Review of Reporting Checklists and Guidelines.

Artificial intelligence (AI) has become increasingly integrated into dental diagnostics, imaging and treatment planning. However, despite this growing adoption, adherence to standardised reporting frameworks remains inconsistent. Insufficient use of established checklists continues to impede reproducibility, transparency and regulatory credibility. This review systematically examines existing AI r...

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 approaches focusing mainly on circulating host cell-free DNA (cfDNA) neglect crucial information within co-existing microbial cell-free DNA (mcfDNA). This review argues for the combined potential of simultaneously analyzing host and microbial signals f...

Deep Learning in Vertebral Fracture Detection: Systematic Review and Meta-analysis of Subject- vs. Vertebra-Level Approaches.

RATIONALE AND OBJECTIVES: To provide a context-aware evaluation of deep learning algorithms for vertebral fracture detection by disentangling subject-...

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-...

Physics-aware imaging AI for quantitative MASLD biomarker mapping: a systematic review of deep learning and radiomics across ultrasound, CT, and MRI.

OBJECTIVE: This systematic review critically appraises the current landscape of physics-aware artificial intelligence (AI) in medical imaging for quan...

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...

Exploring the Endorsement and Implementation of Artificial Intelligence Guidelines in Leading Orthopaedic and Sports Medicine Journals: A Cross-Sectional Study.

BACKGROUND: The integration of artificial intelligence (AI) in orthopaedics and sports medicine (OSM) has transformed clinical practice and scientific...

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 ...

Artificial intelligence in spine care: A scoping review of treatment applications.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in healthcare to support decision-making, personalize treatment, and improve outcomes...

Utility and limitations of the FDA adverse events reporting system public dashboard for safety analyses: a case study with vesicular monoamine transporter 2 inhibitors.

INTRODUCTION: The United States Food and Drug Administration (FDA) requires post-marketing surveillance of approved drugs, and pharmaceutical manufact...

Machine learning models for predicting hospital admission in pediatric emergency departments: A systematic review.

CONTEXT: Pediatric Emergency Departments (PEDs) face overcrowding partially due to delayed hospital admission decision. Machine Learning (ML) models c...

Risk prediction models for adverse drug reactions in pediatrics: a scoping review.

INTRODUCTION: Predictive models play a critical role in enhancing medication safety in clinical practice. While multiple models for adverse drug react...

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...

Co-Designing and Evaluating a Digital Competencies Toolkit for Nursing Students.

AIM: To offer a student-focused critical evaluation of the content and use of a digital competencies discipline-specific toolkit that was co-designed ...

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...

Methodological evaluation and clinical interpretation of hs-cTnI and hs-cTnT variations: a reappraisal.

Recent debates have focused on the impact of analytical imprecision in high-sensitivity cardiac troponin (hs-cTnI and hs-cTnT) assays on the diagnosis...

Machine learning in colorectal cancer prediction and diagnosis: a systematic review of models' performance.

INTRODUCTION: Colorectal cancer (CRC) poses a significant global health burden, demanding early and accurate detection strategies. However, Machine Le...

Screening and machine learning-based prediction of translation-enhancing peptides that reduce ribosomal stalling in Escherichia coli.

We previously reported that the nascent SKIK peptide enhances translation and alleviates ribosomal stalling caused by arrest peptides (APs) such as Se...