Domestic Violence

Design of the first national lung cancer screening program in the European Union: the Croatian Model.

OBJECTIVES: To address Croatia's high lung cancer mortality and late-stage diagnoses, the Ministry of Health initiated a multidisciplinary effort to design a national lung cancer screening program. MATERIALS AND METHODS: Lung cancer remains one of the leading causes of cancer-related mortality both globally and in Croatia. In 2021 alone, Croatia recorded over 3300 new cases of lung cancer and more...

Deep Learning in Vertebral Fracture Detection: Systematic Review and Meta-analysis of Subject- vs. Vertebra-Level Approaches.

RATIONALE AND OBJECTIVES: To provide a context-aware evaluation of deep learning algorithms for vertebral fracture detection by disentangling subject-level from vertebra-level approaches, quantifying the influence of key technical and methodological factors, and generating evidence to guide task-specific clinical use and standardized reporting. MATERIALS AND METHODS: In this PRISMA‑compliant revie...

Machine learning methods for predicting adverse drug events: A systematic review.

Predicting adverse drug events (ADEs) in outpatient settings is crucial for improving medication safety, identifying high-risk patients and reducing h...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for screening adrenal gland volume abnormalities and est...

Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.

BACKGROUND: Use of artificial intelligence chatbots in dental traumatology has increased. However, concerns regarding their reliability are yet to be ...

Characteristics and genomics study of Salmonella isolates in retail chicken in Shaanxi, China: Focus on comparative genomics analysis of S. Kentucky and S. enteritidis isolates from Shaanxi with those from elsewhere in China.

Salmonella is a major foodborne pathogen, frequently linked to poultry and posing serious food safety and public health risks. To investigate its epid...

Perspectives on screening in retinopathy of prematurity: new algorithms and AI tools.

Retinopathy of prematurity (ROP) is a vasoproliferative blinding disorder of the retina, unique to premature infants and a leading cause of preventabl...

Revisiting KANET in the context of fetal connectomics: defining optimal gestational windows for neurodevelopmental screening.

OBJECTIVES: To introduce the KANET-connectome matrix (KANET-Con) as a conceptual framework linking fetal behaviors observed on four-dimensional (4D) u...

Comparative Performance of YOLO Models in the Automated Segmentation of Dental Traumas on Panoramic Radiographs.

OBJECTIVE: This study aimed to compare the performance of artificial intelligence-based deep convolutional neural networks, YOLOv8, YOLOv11, and YOLOv...

Healthbots for conducting clinical screening and remote monitoring with patient mood assessment: A scoping review.

BACKGROUND: Patient mood assessment is key in managing chronic diseases but is often overlooked. Although conversational agents enhance telemonitoring...

Exploring the Endorsement and Implementation of Artificial Intelligence Guidelines in Leading Orthopaedic and Sports Medicine Journals: A Cross-Sectional Study.

BACKGROUND: The integration of artificial intelligence (AI) in orthopaedics and sports medicine (OSM) has transformed clinical practice and scientific...

An Algorithm to Avoid Missed Bowel Injuries in Blunt Abdominal Trauma Patients.

UNLABELLED: Bowel injuries following blunt abdominal trauma (BAT) are evasive to detect clinically and with current imaging modalities. These injuries...

Use of Expected Utility to Evaluate Artificial Intelligence-Enabled Rule-out Devices for Mammography Screening.

BackgroundAn artificial intelligence (AI)-enabled rule-out device may autonomously remove patient images unlikely to have cancer from radiologist revi...

AI-assisted literature screening: A hybrid approach using large language models and retrieval-augmented generation.

OBJECTIVE: Current systematic literature reviews largely rely on manual screening of articles retrieved through keyword search, which is time-consumin...

Regulatory Challenges and Opportunities: A Review of U.S. Food and Drug Administration-Approved Artificial Intelligence and Machine Learning-Enabled Cardiovascular Devices.

The integration of artificial intelligence (AI) and machine learning (ML) into medical devices has revolutionized healthcare, enhancing diagnostic acc...

Screening tools and strategies for early detection of oral cancer and potentially malignant disorders in rural and low-resource populations: A systematic review.

Oral cancer and its precursor lesions, known as oral potentially malignant disorders (OPMDs), present significant public health challenges due to high...

Artificial intelligence in spine care: A scoping review of treatment applications.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in healthcare to support decision-making, personalize treatment, and improve outcomes...

Machine learning identifies traumatic experiences as being associated with auditory verbal hallucinations in both a non-clinical population and individuals diagnosed with psychosis.

BACKGROUND: Auditory verbal hallucinations (AVHs) are a core symptom of psychosis but their prevalence in the general population ranges from 5-28 %. M...

Utility and limitations of the FDA adverse events reporting system public dashboard for safety analyses: a case study with vesicular monoamine transporter 2 inhibitors.

INTRODUCTION: The United States Food and Drug Administration (FDA) requires post-marketing surveillance of approved drugs, and pharmaceutical manufact...

Machine learning models for predicting hospital admission in pediatric emergency departments: A systematic review.

CONTEXT: Pediatric Emergency Departments (PEDs) face overcrowding partially due to delayed hospital admission decision. Machine Learning (ML) models c...