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Domestic Violence

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

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Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score.

BACKGROUND: Traumatic injuries are a leading cause of morbidity and mortality globally, with a dispr...

Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.

BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in impr...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-trau...

Development and validation of machine learning models for MASLD: based on multiple potential screening indicators.

BACKGROUND: Multifaceted factors play a crucial role in the prevention and treatment of metabolic dy...

MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

BACKGROUND: Many chemical releases are first noticed by community members, but reporting these conce...

Cell clone selection-impact of operation modes and medium exchange strategies on clone ranking.

Bioprocessing has been transitioning from batch to continuous processes. As a result, a considerable...

Predicting fall parameters from infant skull fractures using machine learning.

When infants are admitted to the hospital with skull fractures, providers must distinguish between c...

Factors Associated with Abusive Head Trauma in Young Children Presenting to Emergency Medical Services Using a Large Language Model.

OBJECTIVES: Abusive head trauma (AHT) is a leading cause of death in young children. Analyses of pat...

A Paradigm of Computer Vision and Deep Learning Empowers the Strain Screening and Bioprocess Detection.

High-performance strain and corresponding fermentation process are essential for achieving efficient...

Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach.

BACKGROUND: Breast cancer screening plays a pivotal role in early detection and subsequent effective...

Novel Machine-Learning Modeling of Facial Trauma Volume With Regional Event and Weather Data.

OBJECTIVE: Facial trauma volume is difficult to predict accurately. We aim to understand the capacit...

Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data.

Diagnosing Alzheimer's disease (AD) through pathological markers is typically costly and invasive. T...

Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still...

Machine Learning-Assisted High-Throughput Screening of Nanozymes for Ulcerative Colitis.

Ulcerative colitis (UC) is a chronic gastrointestinal inflammatory disorder with rising prevalence. ...

AI image analysis as the basis for risk-stratified screening.

Artificial intelligence (AI) has emerged as a transformative tool in breast cancer screening, with t...

UniAMP: enhancing AMP prediction using deep neural networks with inferred information of peptides.

Antimicrobial peptides (AMPs) have been widely recognized as a promising solution to combat antimicr...

A benchmark of deep learning approaches to predict lung cancer risk using national lung screening trial cohort.

Deep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer ...

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