Domestic Violence

Artificial intelligence-driven prostate cancer diagnosis: Enhancing accuracy and personalizing patient care.

Prostate cancer remains a major global burden; diagnostic pathways rely on prostate-specific antigen (PSA), multiparametric magnetic resonance imaging (mpMRI), and histopathology but face false positives, interobserver variability, and risk of overtreatment. We conducted a narrative review of peer-reviewed human studies (2015-February 2025; PubMed, Web of Science, Google Scholar) on artificial int...

LI-RADS-aligned artificial intelligence for liver cancer diagnosis: methods, evidence, and clinical readiness.

Liver tumor diagnosis relies heavily on imaging, and the liver imaging reporting and data system (LI-RADS) provides a structured framework for evaluating hepatocellular carcinoma (HCC) and related entities in at-risk populations. Artificial intelligence (AI) has rapidly expanded across CT, MRI, and ultrasound/CEUS, yet its clinical credibility depends on adherence to modality-appropriate tasks, ro...

Strategizing AI utilization for psychological literature screening: A comparative analysis of machine learning algorithms and key factors to consider.

With the rapid growth of scholarly literature, efficient artificial intelligence (AI)-aided abstract screening tools are becoming increasingly importa...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Targeting High-Risk Populations for Abdominal Aortic Aneurysm Screening: A Sex-Stratified Analysis in an Ethnicity Diverse Cohort Incorporating Machine Learning Tools.

BACKGROUND: Abdominal aortic aneurysm (AAA) is usually asymptomatic, but rupture carries up to 90% mortality. Ultrasound screening reduces rupture-rel...

The actual performance of ML/AI models in predicting radiation-induced toxicity in head and neck cancer: a systematic review and meta-analysis.

An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RIT...

Artificial Intelligence-Based Delirium Prediction Model for Post-Cardiac Surgery Patients: A Scoping Review.

BACKGROUND: Delirium is a common complication following cardiac surgery and significantly affects patient prognosis and quality of life. Recently, the...

Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.

OBJECTIVE: To compare acceptability of 2 artificial intelligence (AI) use cases in the English National Health Servic Breast Screening Program. PATIEN...

Sociodemographic Predictors of Child-Parent Agreement on Oral Health.

BACKGROUND: Oral health is vital for children's overall well-being. Parents play a critical role in shaping children's oral health through preventive ...

Diagnostic modalities in pediatric obstructive sleep apnea: A review article.

BACKGROUND: Pediatric obstructive sleep apnea (OSA) affects ∼3 % of children and causes adverse neurocognitive, behavioral, and cardiovascular outcome...

Advances in endometrial cancer screening: a comprehensive review of current methods and emerging technologies.

Endometrial cancer represents a major global health concern, with rising incidence particularly in developed countries despite declining mortality rat...

Predictive Modeling of Cancer Information Overload and Screening Attitudes: A Cross-Sectional Study.

OBJECTIVE: To explore the association between cancer information overload and attitudes toward cancer screening among internal medicine patients. AIMS...

Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea.

South Korea, now a "super-aged" society, faces a rising burden of fragility fractures, yet underdiagnosis remains a major barrier, with limited DXA ac...

Industry 6.0 capabilities in orthopaedics: Towards hyper-personalized and autonomous surgical care.

BACKGROUND: Industry 6.0 represents the next frontier in technological evolution, integrating artificial intelligence (AI), autonomous robotics, digit...

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...

Generative artificial intelligence provides accurate case selection in veterinary retrospective studies.

OBJECTIVE: To evaluate the agreement of automation tools with expert evaluators in identifying cases meeting inclusion and exclusion criteria for retr...

Computer-vision based recognition of cervical spine stabilization during trauma resuscitation.

BACKGROUND: Cervical spine (c-spine) injuries can lead to significant disability and mortality. Although stabilization is the primary management for s...

Quantitative EEG enhances early assessment and prognostic stratification of brain dysfunction in infants with abusive head trauma.

AIM: To assess the value of quantitative EEG (qEEG) as a diagnostic and prognostic biomarker in infants with abusive head trauma (AHT). Despite its ce...

Evaluation of AI for prostate cancer detection in biparametric-MRI screening population data.

OBJECTIVE: The goal of this study was to curate a prostate MRI dataset from a screening population and to train and evaluate a deep-learning segmentat...

Persistent dysmorphology and dysfunction of the brain microvasculature following repeated trauma.

Mild traumatic brain injury typically produces no abnormalities on neuroimaging yet elicits symptoms that, in an increasing fraction of survivors, lin...