Refractive Surgery

An interpretable machine learning model for predicting postoperative hypotension in type 2 diabetes mellitus undergoing non‑cardiac surgery.

BACKGROUND: Postoperative hypotension (POH) is a common and serious complication in patients with type 2 diabetes mellitus (T2DM) undergoing non‑cardiac surgery, yet predictive tools tailored to this high‑risk population remain scarce. METHODS: This single‑center cohort study developed and validated a machine learning (ML) model to predict the risk of postoperative hypotension (POH) occurring duri...

Association between dynamic digital radiography findings and post-extubation respiratory deterioration: A retrospective exploratory analysis of a prospectively collected ICU cohort.

INTRODUCTION: Dynamic Digital Radiography (DDR) is a novel bedside imaging modality that enables real-time visualization of pulmonary motion with minimal radiation exposure. We evaluated whether DDR-derived parameters could assist in stratifying the risk of post-extubation respiratory deterioration in ICU patients. METHODS: We analyzed a prospectively collected, single-center cohort of consecutive...

Reimagining Dental Education: Integrating Digital Technologies for a Global, Digitally Native Generation-A Perspective.

ABSTRACT: Digital technologies, such as artificial intelligence (AI), virtual reality (VR), and haptic simulation, are rapidly reshaping oral health e...

A four-gene signature for diagnosis of acute kidney injury following kidney transplantation.

Acute kidney injury (AKI) is a common and severe complication following renal transplantation, largely driven by ischemia-reperfusion injury (IRI). Ho...

Adoption of artificial intelligence tools among pharmacy students in Syria: patterns of use, educational perceptions, and institutional barriers.

BACKGROUND: Artificial intelligence tools are reshaping global higher education, yet their deployment and systemic implications within resource-constr...

Post-Pandemic Forecasting of Pediatric Acute Respiratory Infections with Deep Learning: A Multi-Pathogen, Multi-Time-Horizon Study.

BACKGROUND: Acute respiratory infections (ARIs) remain a major cause of morbidity and hospitalization in children worldwide. In the post-COVID-19 era,...

A donor-recipient ranking model to optimize long-term survival post liver transplant.

Liver transplant (LT) is a life-saving treatment for patients with cirrhosis and/or hepatocellular carcinoma (HCC), but organ shortages and suboptimal...

Deep Learning-Based Prediction of Heart Failure Readmission Using Longitudinal Cardiac Device Data.

BACKGROUND: Heart failure (HF) is a leading cause of hospitalization and readmission. Cardiac implantable electronic devices (CIEDs) continuously capt...

Fusion prediction model for post-ERCP pancreatitis under NSAIDs prophylaxis.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is a common procedure for treating biliary and pancreatic disorders; however, it is ...

Longitudinal validation of ENLIGHT, an AI predictor of immunotherapy response and resistance, in pan-cancer cohorts.

Artificial intelligence (AI) algorithms such as ENLIGHT and DeepPT represent promising approaches to identify predictive biomarkers for immune checkpo...

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 a...

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...

Interpretable machine learning models for predicting perioperative myocardial injury in non-cardiac surgery.

AIMS: Perioperative myocardial injury (PMI) is a frequent and often asymptomatic complication after non-cardiac surgery and is associated with increas...

From Burden to Balance: Trends in Documentation Workload with Ambient AI Scribe Adoption.

BACKGROUND: Physician burnout, often driven by documentation burden in electronic health records (EHRs), remains a major challenge in clinical care. A...

Predicting the Onset of Myopia in Children and Adolescents Using Artificial Intelligence: A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence (AI) models have been used to predict myopia onset, but results are inconsistent. This systematic review and meta-...

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...

[Research progress in diagnostic key points of pediatric pathological myopia].

Pathological myopia has become one of the leading causes of irreversible blinding eye disease in China, yet its early diagnosis, especially in childre...

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...

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...

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...