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Domestic Violence

Latest AI and machine learning research in domestic violence for healthcare professionals.

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Diagnosis and Screening of Velocardiofacial Syndrome by Evaluating Facial Photographs Using a Deep Learning-Based Algorithm.

BACKGROUND: Early detection of rare genetic diseases, including velocardiofacial syndrome (VCFS), is...

Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and...

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly...

Drug-induced torsadogenicity prediction model: An explainable machine learning-driven quantitative structure-toxicity relationship approach.

Drug-induced Torsade de Pointes (TdP), a life-threatening polymorphic ventricular tachyarrhythmia, e...

Screening COPD-Related Biomarkers and Traditional Chinese Medicine Prediction Based on Bioinformatics and Machine Learning.

PURPOSE: To employ bioinformatics and machine learning to predict the characteristics of immune cell...

A Machine Learning Algorithm Suggests Repurposing Opportunities for Targeting Selected GPCRs.

Repurposing utilizes existing drugs with known safety profiles and discovers new uses by combining e...

Future of service member monitoring: the intersection of biology, wearables and artificial intelligence.

While substantial investment has been made in the early identification of mental and behavioural hea...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Ma...

Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.

Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artif...

Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose.

RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate dia...

Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking.

The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of s...

An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.

Current imaging methods for diagnosing breast cancer (BC) are associated with limited sensitivity an...

Screening of genes co-associated with osteoporosis and chronic HBV infection based on bioinformatics analysis and machine learning.

OBJECTIVE: To identify HBV-related genes (HRGs) implicated in osteoporosis (OP) pathogenesis and dev...

Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displ...

Benchmarking Human-AI collaboration for common evidence appraisal tools.

BACKGROUND AND OBJECTIVE: It is unknown whether large language models (LLMs) may facilitate time- an...

Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study.

We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired che...

Assessing the Reporting Quality of Machine Learning Algorithms in Head and Neck Oncology.

OBJECTIVE: This study aimed to assess reporting quality of machine learning (ML) algorithms in the h...

On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

Protein design and directed evolution have separately contributed enormously to protein engineering....

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