Domestic Violence

Predicting Elder Abuse Using a Random Forest Classifier.

This paper aims to identify key factors influencing elder abuse within the family and to further explore the heterogeneity of these factors across different types of elder abuse. The data were drawn from the China Longitudinal Aging Social Survey and the final valid sample was 10,703. A random forest classifier, a supervised machine learning method, was employed to identify the key influencing fac...

Diagnostic technologies for neuroblastoma.

Neuroblastoma is an aggressive childhood cancer characterised by high relapse rates and heterogenicity. Current medical diagnostic methods involve an array of techniques, from blood tests to tumour biopsies. This process is associated with long-term physical and psychological trauma. Moreover, current technologies do not identify neuroblastoma at an early stage while tumours are easily resectable....

Deep Learning Photo Processing for Periodontitis Screening.

Late detection of periodontitis has significant health implications. Screening via oral images may serve as an accessible nonclinical method. This stu...

Rapid trauma classification under data scarcity: an emergency on-scene decision model combining natural language processing and machine learning.

Trauma has become a major cause of increased morbidity and mortality worldwide. In emergency response, the classification of injuries is crucial as it...

Artificial Intelligence for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios.

. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examinations are used predominantly for assisting radiolo...

Theory-based chatbot for promoting colorectal cancer screening in a community setting in Hong Kong: study protocol of a randomised controlled trial.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality worldwide. Despite the organised ...

Event-Driven Taxonomy (EDT) Screening: Leveraging Effect-Based Spectral Libraries to Accelerate Semiquantitative Nontarget Analysis of AhR Agonists in Sediment in the Era of Big Data.

Sediments contain complex chemical mixtures. While effect-directed analysis (EDA) combined with nontarget screening (NTS) is promising, its large-scal...

Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.

Cervical cancer stands out among various cancers due to its potential for prevention and eradication, mainly through vaccination and proactive screeni...

Identifying Psychosocial, Self-Management, and Health Profiles Among Women With Chronic Pain Who Have Experienced Intimate Partner Violence and Those Who Have Not: Protocol for a 2-Phase Qualitative and Cross-Sectional Study Using AI Techniques.

BACKGROUND: Women who experience intimate partner violence (IPV) are more likely to develop disabling chronic pain (CP). However, there is little info...

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in trauma-induced coagulopathy.

Despite advancements in trauma care, uncontrolled hemorrhage and trauma-induced coagulopathy (TIC) remain the leading causes of preventable deaths aft...

A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology.

Artificial intelligence (AI) and machine learning (ML) are transforming nephrology by enhancing diagnosis, risk prediction, and treatment optimization...

Promising for patients or deeply disturbing? The ethical and legal aspects of deepfake therapy.

Deepfakes are hyper-realistic but fabricated videos created with the use of artificial intelligence. In the context of psychotherapy, the first studie...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher...

Research on predicting the risk level of coal mine roof accident based on machine learning.

Coal mine roof accidents are one of the main types of accidents leading to the decline of coal mine safety productivity, accounting for about 20% of t...

Employing machine learning for early detection of poly-victimization in rural children: a survey study in China's Chaoshan region.

BACKGROUND: Poly-victimization (PV), encompassing multiple forms of victimization including physical abuse, emotional maltreatment, neglect, and peer ...

Ultrahigh-Throughput Virtual Screening Strategies against PPI Targets: A Case Study of STAT Inhibitors.

In recent years, virtual screening of ultralarge (10) libraries of synthetically accessible compounds (uHTVS) became a popular approach in hit identif...

Enhancing Prostate Cancer Classification: A Comprehensive Review of Multiparametric MRI and Deep Learning Integration.

Multiparametric MRI (mpMRI) has become an essential tool in the detection of prostate cancer (PCa) and can help many men avoid unnecessary biopsies. H...

Can ChatGPT Provide Patient-Friendly and Reliable Information on Cervical Cancer Screening? A Study of ChatGPT-Generated Information in Polish.

BACKGROUND Cervical cancer (CC) mortality remains a global health problem, and women's awareness of the need for regular CC screening is insufficient....

Comparative analysis of artificial intelligence tools for the dissemination of colorectal cancer screening guidelines: a novel perspective on early screening education.

This study systematically evaluated the effectiveness of three artificial intelligence (AI) tools-ChatGPT-4o, Claude3.5, and DeepSeek-in disseminating...

Machine learning-driven prediction of eye irritation toxicity: Integration of in silico and in vitro study.

Eye irritation (EI) toxicity poses critical challenges in chemical safety assessment, demanding alternatives to ethically contentious animal testing. ...