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Factors associated with post-pornography masturbation among university students: a machine-learning study.

BACKGROUND: Pornography consumption is common among university students, yet little research has examined behavioral responses occurring immediately after exposure. Such behaviors may have implications for sexual health, behavioral conditioning and psychosocial well-being. This study investigated the prevalence and correlates of post-pornography masturbation among university students in Bangladesh...

Hazard-portfolio patterns in US food recall severity reveal transferable pathogen signals and firm-specific compliance signals.

The U.S. FDA classifies food recalls into three severity tiers (Class I / II / III), a decision that drives public notification urgency and regulatory resource allocation. Using 28,448 openFDA enforcement records (2012-2025), we investigate the structural determinants of recall severity. Under standard evaluation (Known-firm scenario), a simple baseline assigning each firm its historically most fr...

Data After Death: Post-Mortem Ethics of Burn Patient Records and Images.

Burn care frequently relies on extensive documentation, including graphic photographic images and detailed clinical records. While these materials are...

Diagnosing helminth infections in a large reference laboratory in the United States: a 6-month pre- and post-implementation analysis of AI-augmented screening of concentrated fecal wet mounts.

Helminth infections are uncommon in the United States, yet accurate detection remains critical. Conventional ova-and-parasite examinations are labor-i...

Analytic Misjudgment of Drug Safety Evidence and Causality: From the Prosecutor's Fallacy and Simpson's Paradox to Artificial Intelligence.

Drug safety assessment, particularly in the post-marketing setting, is especially vulnerable to analytic misjudgment because it relies on heterogeneou...

Breaking Barriers in Student Mental Health Care With AI-Enhanced Group Cognitive Behavioral Therapy: Pilot Feasibility Study.

BACKGROUND: University students experience elevated psychological distress, with limited access to mental health services. While cognitive behavioral ...

Stage-transition mechanism of forest-grass vegetation coverage in machine-learning simulation of event-scale suspended sediment concentration processes.

Vegetation restoration is widely regarded as a key measure for mitigating soil erosion in the middle reaches of the Yellow River. However, the regulat...

The Search for Borderline Hearts within Biventricular Repairs of Complete Atrioventricular Septal Defects.

OBJECTIVES: To discover distinct clusters of morphologic features within the spectrum of complete atrioventricular septal defect (cAVSD) among childre...

The current state of demographic subgroup reporting for commercially available AI for radiology: a scoping review.

OBJECTIVE: Though subgroup performance reporting helps ensure the safety of artificial intelligence (AI) products, the extent of this reporting remain...

Machine learning models to predict the recurrence of common bile duct stones after ERCP.

OBJECTIVE: To construct predictive models for the recurrence of common bile duct stones (CBDS) following endoscopic retrograde cholangiopancreatograph...

An AI-Driven H5P Training for Epilepsy Emergency Management Preparedness in Dental Education.

BACKGROUND: Deficiencies in knowledge and skills related to the management of medical emergencies in dental settings can adversely affect the clinical...

Oral and Maxillofacial Surgery research hotspots and emerging trends in 2025: A targeted bibliometric analysis.

OBJECTIVES: To perform a targeted bibliometric analysis of the Oral and Maxillofacial Surgery (OMFS) literature from 2025 to map its current intellect...

Disparities in Engagement with an Artificial Intelligence-Based Chat Intervention Post-appendectomy.

PURPOSE: Artificial intelligence (AI)-based text messaging, or "chat," in post-appendectomy care has been shown to decrease preventable emergency depa...

Predicting long-term allograft outcomes in kidney transplant recipients using a machine learning approach: a 5-year retrospective cohort study.

Long-term outcomes of kidney allografts vary significantly among deceased donor kidney transplant recipients, and current prediction tools struggle to...

Yolov7 neural network for pelvic X-rays after total hip arthroplasty: automatically measuring component position parameters- a retrospective feasibility study.

BACKGROUND: After total hip arthroplasty (THA), regular follow-up X-rays are required to evaluate the position of the prosthesis. However, measuring t...

The entropic brain today.

Introduced in 2014 and revised in 2018, the entropic brain hypothesis has accrued a wealth of supportive evidence. The hypothesis states that-along a ...

Quantification of Histotripsy Dosage Using Machine Learning-Enhanced Ultrasound Imaging Analysis: Correlation with Histological Outcomes.

RATIONALE AND OBJECTIVES: Histotripsy is a noninvasive ultrasound therapy that mechanically disrupts target tissue through controlled acoustic cavitat...

Daily water level forecasting with limited data using cluster- and season-based transfer learning.

The coupling of clustering or classification with deep learning presents an appealing knowledge-guided approach for hydrological prediction. However, ...

Artificial intelligence in 3D bioprinting and biofabrication: a validation-stringency assessment.

Three-dimensional (3D) bioprinting and biofabrication increasingly use artificial intelligence (AI) and machine learning (ML) for bioink formulation, ...

Development and external validation of a machine learning model for predicting post-CABG acute kidney injury: insights from MIMIC database and real-world cardiac surgery cohort.

OBJECTIVE: Acute kidney injury (AKI) is a severe complication following coronary artery bypass grafting(CABG) While machine learning models trained on...