Laser Surgery

[Sarcoidosis-associated uveitis: Current status and future prospects].

Sarcoidosis-related uveitis is the most common manifestation of ocular sarcoidosis. It can occur at any age but preferentially affects adults aged 30 to 60 years, with a female predominance, especially in forms with late onset. Suggestive semiological features are: granulomatous anterior uveitis defined by thick retro-descemetal precipitates (so-called "mutton-fat" keratic precipitates) or iris no...

Semantic edge detection of fractures in geological outcrops using edge aware dilated convolutional networks.

Natural fracture networks govern subsurface fluid flow, rock-mass stability, and strain accommodation in the brittle crust, yet their automated delineation from outcrop imagery remains challenging due to multi-scale size variability, low contrast between fracture boundaries and host-rock texture, and scene clutter from vegetation, shadows, and blast artifacts. Standard encoder-decoder networks app...

Matrix-Aware Electrochemical Sensing: A Neural Network Approach to Deciphering Medium-Specific Surface Dynamics.

Accurate monitoring in complex biofluids remains challenging due to unpredictable skin - electrode interfacial interference and matrix-dependent imped...

Regional differences in foveal avascular zone morphology in cynomolgus macaques using a normative OCTA database.

Cynomolgus macaques are widely used in preclinical ophthalmic research because of their close anatomical and physiological similarity to the human eye...

Oculomics: advances and perspectives from traditional Chinese medicine to modern multimodal biomarkers.

Oculomics, the study of the relationship between ophthalmic biomarkers (changes or abnormalities in the eye) and systemic health or disease states, po...

PanMB2-Net: a deep learning framework for preoperative MB2 canal risk assessment on panoramic radiographs.

OBJECTIVES: This study aimed to develop and validate a clinically motivated artificial intelligence framework for preoperative risk assessment of the ...

Data-centric physics-inspired deep learning framework for saturation artifact removal in optical coherence tomography.

In Fourier-domain optical coherence tomography (FD-OCT) imaging, saturation of the data acquisition chain leads to loss of information by clipping the...

Construction and Applications of Knowledge Graphs in Ophthalmology.

Knowledge Graph (KG) is an artificial intelligence technique that provides a structured representation of medical entities and their relationships, th...

Artificial Intelligence for Predicting Postoperative Outcomes in Anterior Segment and Ocular Adnexa Surgery: A Systematic Review.

TOPIC: Artificial intelligence (AI) is increasingly applied to support decision-making in ophthalmology. This review evaluates the ability of AI to pr...

Precision-Driven Management of Great Saphenous Varicose Veins: A Narrative Review.

OBJECTIVES: Great saphenous vein (GSV) incompetence is common, but numerous treatment options complicate patient-treatment matching. This narrative re...

Deep Learning for Automated 3D Ophthalmic Ultrasound Reconstruction and Probe Path Optimization.

A deep learning framework for recognizing skin changes secondary to chronic venous insufficiency in clinical photographs: a multicentre validation study.

BACKGROUND: Chronic venous insufficiency (CVI) produces heterogeneous lower-extremity skin changes that often mimic inflammatory dermatoses, complicat...

Can ChatGPT Be Trusted for Urologic Patient Education? A Comparative Study of Stress Urinary Incontinence-Related Information From Versions 3.5 and 4.

INTRODUCTION AND HYPOTHESIS: The application of artificial intelligence tools such as ChatGPT in patient education is expanding rapidly. Female stress...

Development of non-destructive durian fruit maturity detection tool based on multi-variable sensor for harvest quality optimisation.

Durian maturity critically affects consumer acceptance, market value, and postharvest losses, yet its assessment remains largely subjective. This stud...

[Artificial intelligence in neuro-ophthalmology: prospects, challenges and countermeasures].

Neuro-ophthalmic disorders feature complex etiology. Certain ocular manifestations may hint at severe neurological diseases. Current clinical practice...

Prediction of microvascular invasion in hepatocellular carcinoma using contrast-enhanced ultrasound and deep learning.

Microvascular invasion (MVI) is a key prognostic factor in hepatocellular carcinoma but is currently only detectable after surgery. Here, we develop M...

Prediction model for recurrent laryngeal nerve injury in microwave ablation of thyroid nodules.

OBJECTIVE: This study aims to develop an explainable machine learning (ML) framework integrating clinical, imaging, and procedural features for predic...

An exploratory SMOTE-SVM approach for identifying preoperative biomechanical risk factors driving early toric intraocular lens micro-rotation in extremely imbalanced cohorts.

The predictive modeling of postoperative mechanical complications, such as the early micro-rotation of premium toric intraocular lenses (IOLs), is sev...

Predicting CO2 injection profiles in heterogeneous reservoirs using a physics-aware deep learning framework.

Accurate prediction of CO2 injection profiles is essential for optimizing injection strategies in heterogeneous reservoirs. However, repeated composit...

Data-scarce transfer learning fusion for positron emission tomography and computed tomography guided lung biopsy.

OBJECTIVES: We developed a transfer learning-based multimodal fusion deep learning model integrating positron emission tomography/computed tomography ...