Refractive Surgery

Anticipating health and care trajectories from routinely collected social care records.

Predictive modelling in healthcare has advanced rapidly, yet social care systems, despite their central role in supporting vulnerable populations, remain underexplored in this domain. In this study, we apply machine learning to a large, pseudonymised dataset of social care records from 27,590 adults in Oxfordshire, encompassing around 90% of individuals receiving care in the region. We developed m...

Robot-assisted biopsy a bibliometric analysis of global trends, hotspots, and emerging frontiers (2000-2025).

Robot-assisted biopsy techniques achieve precise minimally invasive sampling of deep-seated and anatomically complex lesions through stable robotic manipulation, intelligent path planning, and multimodal imaging fusion. These techniques have accumulated substantial evidence in urology, neurosurgery, and thoracic intervention. However, the field spans multiple organs and technical directions, and l...

Community-based paediatric eye care in low- and middle-income countries: bridging the gap between policy and practice.

Childhood visual impairment and blindness remain major public health concerns in low- and middle-income countries (LMICs), despite a substantial propo...

Stigmatizing Language in Gender-Expansive Patient Records: Corpus Development, Disparity Analysis, and Natural Language Processing-Based Detection Study.

BACKGROUND: Stigmatizing language (SL) in electronic health records (EHRs) can influence clinical decision-making, propagate bias across care encounte...

"Objectifying Outcomes in Facial Aesthetic Surgery Using Artificial Intelligence".

BACKGROUND: Choosing which procedure or combination of procedures is appropriate remains a daunting task for patients and surgeons alike. The goal of ...

Deciphering Post-surgery Gut Microbial Dynamics in Colorectal Cancer through Multi-cohort Machine Learning.

Surgical resection, and its associated bowel preparation, remain the primary treatment for colorectal cancer (CRC), yet the associated effects on post...

Improved Deep Learning Segmentation of Pediatric Diffuse Midline Gliomas After Treatment.

PURPOSE: To develop and validate a pediatric diffuse midline glioma (DMG) auto-segmentation tool optimized for longitudinal treatment response assessm...

Predicting social media post popularity using multimodal deep learning: Insights from content features.

This study predicts social media post popularity by examining the associations between multimodal, unstructured content features and observed engageme...

Electrodermal signatures of stress during tactical law enforcement training.

Law enforcement tactical training places sustained cognitive and emotional demands on recruits, making stress regulation a critical determinant of lea...

tDCS synchronous robotic training on lower-limb with post-stroke hemiplegia: a comparative study between synchronous and sequential group.

BACKGROUND: This study was aimed to compare the effects of tDCS synchronized with robotic training(RT)and tDCS sequential followed by RT on lower-limb...

A clinician-centered evaluation framework for large language models in patient education: Integrating the Technology Acceptance Model and Medical Condition Regard Scale.

Inadequate post-care patient education contributes to preventable readmissions and adverse outcomes that disproportionately affect medically complex, ...

Machine Learning-Based Prediction of Cycloplegic Refraction Using the Eyerobo Vision Screener: Design-A Cross-Sectional Comparative Device Study.

INTRODUCTION: A cross-sectional comparative device study to compare the Eyerobo Vision Screener (VS), a portable handheld photorefractor, against a co...

A decade of artificial intelligence research in ophthalmology: Global trends and transferable insights for medical AI.

To characterize global trends in ophthalmic AI research from 2015-2025 and drive transferable insights into the broader evolution of AI in medicine, w...

Identification and risk-factor analysis for individuals at high risk for keratoconus via machine learning and logistic regression.

PURPOSE: To evaluate keratoconus (KC) risk factors and to develop a machine-learning (ML) model for KC and myopia classification. METHODS: In this ret...

Pathogenic Genetic Variants, Comorbid Autism and Adaptive Developmental Quotient as Independent Predictors of Intellectual Disability in Children With Global Developmental Delay: An Interpretable Machine Learning Model With Calibrated Risk Estimation.

BACKGROUND: Global developmental delay (GDD) frequently precedes intellectual disability (ID), but no validated multivariable prognostic tool exists t...

Personalized adaptive virtual reality experience driven by electroencephalography-based pain recognition.

BACKGROUND: Non-pharmacological pain management represents an urgent clinical need. Emerging technologies such as virtual reality (VR) and electroence...

Stress hyperglycaemia ratio and post-operative delirium after cardiac surgery: a retrospective cohort study of the MIMIC-IV database.

BACKGROUND: Post-operative delirium is a serious neurocognitive complication of cardiac surgery. The stress hyperglycaemia ratio (SHR), which adjusts ...

Integrative single-cell sequencing and machine learning analyses identify chronic inflammation and cancer-associated fibroblast subsets as drivers of adverse outcomes in ovarian cancer.

BACKGROUND: Ovarian cancer remains the deadliest gynecological malignancy, with neoadjuvant chemotherapy (NACT) often leaving residual fibroblast-enri...

Identification and localization of myopic macular neovascularization using deep learning.

PURPOSE: Myopia is rapidly increasing worldwide, with macular neovascularization (MNV) representing a major cause of vision loss. Early diagnosis rema...

Predicting patient satisfaction with post-small incision lenticule extraction surgery using open-source machine learning software.

OBJECTIVE: To predict patient satisfaction 6 months after small-incision lenticule extraction (SMILE) surgery from preoperative clinical data demonstr...