Refractive Surgery

Using deep learning to explore the impacts of street-view green space on school myopia prevalence: a multicenter, cross-sectional study.

Predictive machine learning algorithms for depression and anxiety disorders in six cancer types: a comprehensive multi-center population-based study.

OBJECTIVE: Machine learning (ML) has advanced predictive modeling in medical diagnosis and risk assessment through large clinical datasets, yet applications for predicting post-cancer depression and anxiety remain limited. This cross-institutional, longitudinal study aims to develop ML models to predict depression and anxiety in cancer patients and to identify key contributing factors. METHODS: ML...

Effectiveness of transcranial direct current stimulation (tDCS) on attention and memory biases in individuals with post-traumatic stress disorder (PTSD): a randomized, single-blind, parallel-group study.

Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...

Explainable multimodal deep learning models for variable-length sequences in critically ill patients.

OBJECTIVE: Deep learning models have shown strong performance in predicting clinical events in critical care using structured electronic health record...

Beyond pre-travel risk assessment: machine learning for clinical diagnosis in returned travellers.

Machine learning (ML) applications in post-travel clinical care remain limited. ML-based models show good diagnostic performance for malaria when clin...

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mech...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Improved outcomes and donor utilization in heart transplantation with 10 °C static cold storage.

OBJECTIVE: To compare 10 °C static cold storage (SCS) with traditional ice for cardiac allograft preservation, its impact on post-transplant outcomes,...

Lean mass loss in the intensive care unit and its restoration: A narrative review.

The preservation of lean mass (LM) and its restoration following catabolic loss represents a primary challenge for clinical nutrition in critically il...

Is the FDA regulation of cardiology AI devices supporting cardiovascular innovation: a scoping review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have shown immense potential in cardiology, leveraging data-driven insights to enha...

Dynamic Ex-Post Baselines for Enhancing the Credibility of Improved Forest Management Carbon Offsets.

Forest carbon offsets are pivotal to the global climate strategy, yet their claimed benefits are often undermined by flawed baselines, compromising th...

A comprehensive review of non-destructive technologies for banana ripeness assessment: implications for food quality, safety, and supply chain management.

Banana (Musa spp.) is a primary climacteric fruit characterized by a rapid surge in ethylene production and respiration post-harvest. Accurate ripenes...

Artificial intelligence facilitated smile design for the rehabilitation of a fully maxillary edentulous patient with a complete arch implant-supported prosthesis: A dental technique.

This dental technique describes the use of an artificial intelligence (AI)-facilitated digital workflow in the rehabilitation of an edentulous maxilla...

Reimagining intensive care unit recovery: The Critical Illness Survivorship Programme for humanising post-intensive care unit care - A discussion paper.

BACKGROUND: Survivorship after critical illness is often characterised by fragmented recovery and lingering cognitive, psychological, and physical imp...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

3D Cardiac Magnetic Resonance Substrate Features-Based Machine Learning Model for Post-myocardial Infarction Risk Stratification: a Multicenter Study.

BACKGROUND: Accurate risk stratification post-myocardial infarction (MI) remains challenging. This study aimed to develop interpretable machine learni...

Multidimensional analysis of postoperative nursing challenges in oral cancer surgery: a retrospective study of 245 patients and proposal of the PROTECT mode.

PURPOSE: The quality of postoperative care for oral tumors critically influences patient prognosis and quality of life; however, current nursing syste...

The AI Act and the MDR post-market requirements for semiautonomous AI SaMD: a radiology case study in prostate cancer.

PURPOSE: To clarify overlapping post-market obligations under the EU Artificial Intelligence Act (AIA) and EU Medical Device Regulation (MDR) for high...

Multi-branch convolutional neural network and intracranial EEG high-frequency oscillations predict post-surgical seizure outcomes.

OBJECTIVE: Pathological High-Frequency Oscillations (HFOs) identify epileptogenic cortex, but their surgical utility is unproven. Current epilepsy sur...

AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support.

BACKGROUND: CRISPR-based genetic screening has become a central methodology in functional genomics, enabling systematic interrogation of gene function...