Domestic Violence

BiToxNet: a deep learning framework integrating multimodal features for accurate identification of neurotoxic peptides and proteins.

BACKGROUND: Accurate prediction of the neurotoxicity of peptides and proteins is critically important for the safety assessment of protein therapeutics and the development of protein-based drugs. Although experimental methods can reliably identify neurotoxic peptides and neurotoxins, they are labor-intensive, costly, and unsuitable for large-scale screening. Existing computational approaches are o...

Assessing the completeness of reporting in imaging studies using artificial neural network models for cancer diagnosis: Adherence to the TRIPOD-AI guideline.

BACKGROUND: Developments in artificial neural networks (ANNs) offer significant promise for cancer screening and risk prediction, with the potential to improving patient outcomes. Ensuring complete and transparent reporting of study methodologies is important for ensuring model reproducibility. This review aims to evaluate the completeness of reporting of imaging studies that utilise ANN models fo...

Data mining in pediatric radiology in the era of artificial intelligence.

Data mining is the systematic process of extracting useful knowledge from large multimodal datasets and is increasingly enabled by artificial intellig...

A Novel Hybrid Large Language Model Approach for Reporting Panoramic Radiographs and Performance Comparison with Current Large Language Models.

Large language models (LLMs) show potential in clinical reporting, yet current multimodal systems remain unreliable for interpreting panoramic radiogr...

Integrated virtual screening, machine learning and molecular dynamics identify novel phytochemical FabI inhibitors against MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical global health threat, necessitating the discovery of novel antibacterial...

From conventional screening to self-driving discovery: Organ-on-Chip platforms as engines for AI-guided nanomedicine.

Nanoparticles have become an essential platform for next-generation drug delivery and therapeutic development, yet clinical translation remains limite...

Screening for Breast Cancer: Imaging Updates.

This article provides a comprehensive overview of breast cancer screening guidelines and the evolving role of established and emerging imaging technol...

Machine learning in trauma anesthesia - from promise to practice.

Longitudinal multisource clinical model for early lung cancer risk stratification and screening.

OBJECTIVES: Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current s...

A systematic review on dysconnectivity in face and emotion processing networks in schizophrenia.

Schizophrenia is a complex psychiatric disorder that affects approximately 20 million people worldwide. Patients show face-processing deficits that si...

Two -stage contrastive learning framework for vertebral compression fracture screening in frontal chest X-ray.

Vertebral Compression Fractures (VCFs) are early signs of osteoporosis and the most common type of osteoporotic fracture. In clinical practice, the pi...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Can AI write reports like a radiologist? A blinded evaluation of large language model-generated lumbar spine MRI reports.

BACKGROUND: To compare the quality and clinical usefulness of large language model (LLM)-generated lumbar spine magnetic resonance imaging (MRI) repor...

AI-Driven Patient Screening for Clinical Trials in Pancreatic Cancer: The PANCR-AI Pilot Retrospective Comparative Study.

BACKGROUND: Screening for clinical trials is challenging for clinicians due to its time-consuming and repetitive nature. The rise of artificial intell...

AI and Wearables for Early Detection of Cognitive Impairment and Dementia: Systematic Review.

BACKGROUND: Traditional cognitive screening relies on episodic clinical assessments and may miss early changes preceding cognitive impairment and deme...

Machine learning and metabolic signatures of drowning: A pathway to uncovering cause of death in aquatic environments.

The postmortem diagnosis of drowning is challenging due to the nonspecific and transient nature of classical autopsy findings. This study aimed to inv...

Multivariate feature analysis of early-stage laryngeal cancer serum components using surface-enhanced Raman spectroscopy.

Laryngeal cancer is a common head-and-neck malignant tumor with geographically variable incidence. Its lack of specific early clinical symptoms often ...

Efficient self-supervised Barlow Twins from limited tissue slide cohorts for colonic pathology diagnostics.

Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50...

Prospective pilot evaluation of a deep learning model for kidney stone detection on CT using a web-based workflow platform.

Rapid and reliable detection of kidney stones on non-contrast abdominal CT is essential for timely decision-making in emergency radiology. However, ri...

Machine learning-assisted abstract screening on learning analytics: a step-by-step tutorial.

Systematic reviews are crucial for synthesizing evidence, but their manual processes, particularly abstract screening, are labor-intensive and prone t...