Identifying and Reporting Dependent Adult abuse

Quantum-enhanced throughput pathways: Integrating Rodgers' TPM with quantum ethical frameworks for AI-driven cybersecurity.

This integrative conceptual review synthesizes psychological, ethical, and quantum-information perspectives to advance Quantum-Enhanced Throughput Modeling (Q-TPM) as a novel framework for ethical decision-making in AI-driven post-quantum cybersecurity. Building on Rodgers' Throughput Model (TPM), Q-TPM embeds quantum-inspired mechanisms, superposition for concurrent ethical pathway activation, en...

Artificial intelligence-enabled "inherited noninvasive intracellular recording" for prolonged monitoring of cardiac action potentials.

Intracellular action potential (AP) recording that allows long-term monitoring is challenging because permanent membrane penetration is impossible due to cell death or resealing of perforated cell membrane. Herein, an "inherited noninvasive intracellular recording" methodology was proposed, which was based on the fusion of artificial intelligence (AI) with microelectrode array (MEA)-electroporatio...

How to Evaluate the Accuracy of Symptom Checkers and Diagnostic Decision Support Systems: Symptom Checker Accuracy Reporting Framework (SCARF).

Symptom checkers are apps and websites that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When...

Biometric Data in Post-Traumatic Stress Disorder Detection: A Scoping Review of Digital Health Applications.

CONTEXT: Post-traumatic stress disorder (PTSD) is mainly assessed through self-reports and clinician interviews, which can delay recognition and limit...

Artificial Intelligence in Snoring Sound Analysis: OSA Detection and Obstruction Site Classification, a Systematic Review.

OBJECTIVE: The aim of the systematic review is to evaluate the application of machine learning (ML) and artificial intelligence (AI) models in the ana...

Machine learning for the prediction of atrial fibrillation recurrence after catheter ablation: A systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: This systematic review evaluates the current state of Machine Learning (ML) methods for predicting Atrial Fibrillation (AF) ...

Data-driven prediction of child neglect and abuse using integrated municipal sources.

BACKGROUND: Child neglect and abuse are prevalent worldwide yet often incompletely reported and are frequently associated with long-term adverse physi...

Artificial Intelligence in the Laminate-Veneer Workflow: A Systematic Review and Meta-Analysis of Accuracy, Efficiency, and Esthetic Predictability.

BACKGROUND: Artificial intelligence (AI) technologies are increasingly incorporated into restorative and esthetic dentistry; however, their reliabilit...

Evaluating the efficacy and diagnostic reliability of computer vision artificial intelligence algorithm in automating anatomical classification for second-trimester fetal anomaly ultrasound scans: A prospective cohort study.

OBJECTIVE: To evaluate the diagnostic accuracy and workflow efficiency of BioticsAI-anatomyUNet-0.1-2022 software in identifying 18 standard fetal ana...

SupReMix: Supervised contrastive learning for medical imaging regression with mixup.

In medical image analysis, regression plays a critical role in computer-aided diagnosis. It enables quantitative measurements such as age prediction f...

Pediatric asthma management via integration of a remote spirometry device into an EHR-based artificial intelligence-powered clinical decision support system: A feasibility pragmatic clinical trial.

BACKGROUND: Asthma is the most common chronic disease in children. Suboptimal asthma control is prevalent and causes significant health care costs. El...

Machine Learning- and AI-Driven QSAR Models for the Discovery of Novel Potential Fungicides: FAPI (Fungicide Targeting Acid Phosphatase Inhibition).

Fungal pathogens like Podosphaera xanthii (powdery mildew) and Botrytis cinerea (gray mold) cause significant agricultural losses, with fungicide resi...

Methodological Variations in 24-Hour Urine Collection for Nephrolithiasis: A Systematic Review of Reporting Practices and Clinical Implications.

BACKGROUND: A 24-hour urine collection is central to the metabolic evaluation and prevention of nephrolithiasis. Despite its widespread use, methodolo...

Predicting molecular types of adult-type diffuse gliomas based on MRI reports with large language models.

OBJECTIVES: To evaluate the performance of large language models (LLMs) in predicting molecular types of adult-type diffuse gliomas according to the 2...

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...

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 evaluat...

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...

Advancing mold identification in the routine laboratory, performance of smartphone-based imaging and a newly developed convolutional neural network.

Mold identification in clinical diagnostics is traditionally labor-intensive and is dependent on expert interpretation. MoldVision is a deep-learning ...

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 ...