Ophthalmology

Development of artificially intelligent tool for analysis and prediction of myopia progression among school-going children.

BACKGROUND: Myopia is a growing public health concern among school-going children, with increased screen time and reduced outdoor activities contributing to its early onset and rapid progression. In India, the absence of a standardized, population-based dataset reflecting socio-economic and environmental diversity limits the development of accurate prediction tools. This study aims to design and v...

Clinicopathological and Imaging Distinction Between Ocular Adnexal MALT Lymphoma and IgG4-Related Ophthalmic Disease.

PURPOSE: To characterize clinicopathologic and imaging differences between ocular adnexal mucosa-associated lymphoid tissue lymphoma (OAML) and IgG4-related ophthalmic disease (IgG4-ROD) and to evaluate clinical and artificial intelligence-assisted approaches for differentiating these entities. DESIGN: Retrospective, single-center observational cross-sectional study. PARTICIPANTS: Four hundred pat...

Artificial intelligence in healthcare, dentistry, and orthodontics; is it an opportunity or a threat? An epistemological review.

Helpless, the human race stands in front of Artificial Intelligence (AI) that has invaded us and evaded our defences, leaving the world stranded and s...

Stakeholder Perspectives of Implementation Barriers of Artificial Intelligence in Eye Care: A qualitative framework-based study.

PURPOSE: Despite the revolution of artificial intelligence (AI), its integration remains limited in healthcare. A comprehensive understanding of the b...

Nanowire photodetectors: path to single physical artificial neurons.

Neurons are basic units for information processing in biological systems. Inspired by the information-processing efficiency of biological systems, art...

Deep learning based eye disease classification using Optical Coherence Tomography (OCT) images.

BACKGROUND AND OBJECTIVE: Optical Coherence Tomography (OCT) imaging plays a crucial role in the early diagnosis of ocular diseases. This study aims t...

Neuromodulation of the central nervous system for facial pain.

Chronic craniofacial pain can lead to significant morbidity and reduced quality-of-life. Refractory pain subsequently leads to maladaptive changes wit...

TearNET: Validation of a convolutional neural network for grading of tear ferning patterns using deep learning.

PURPOSE: Tear-ferning patterns are microscopic crystallization formed when the solvent in the tears evaporates, and the solutes congregate to form a f...

Accurate diagnosis of non-small cell and small cell lung cancer by using machine learning models trained with physical science features extracted from pathological images.

BACKGROUND: Accurate differentiation between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) is crucial for optimising treatment ...

Tear fluid multi-omics and biosensor integration for diagnosis and personalized therapeutics in dry eye disease.

Dry Eye Disease (DED) is increasingly recognized as a complicated, multi-factorial disease involving oxidative damage, metabolic dysregulation and imm...

A hybrid framework for effective microscopic cell counting segmentation integrating Light-U-net with watershed.

Glaucoma is a major cause of irreversible blindness worldwide, resulting in the progressive degeneration of retinal ganglion cellss (RGCs), which make...

Predicting 10-2 SITA Standard from 24-2C SITA Faster: Development and Validation of Deep24-2C.

PURPOSE: To develop and validate Deep24-2C, a machine learning (ML) model that reconstructs comprehensive Humphrey Field Analyzer (HFA) 10-2 visual fi...

Code-Based Versus AutoML Methods for Pill Recognition in Clinical Settings: Comparative Performance Study.

BACKGROUND: Visual identification and verification of medications during dispensing and administration are prone to human error, particularly in high-...

Lesion Learning Network with Relation Aware Transformer for Diabetic Retinopathy Grading.

Diabetic Retinopathy (DR) is a leading cause of permanent blindness due to the difficulty of early screening. In this context, deep-learning-based aut...

An Open-Source Deep Learning Framework for Automated Corneal Segmentation in Anterior Segment Optical Coherence Tomography With Cross-Device External Validation.

PURPOSE: To develop a deep learning model-Cornea nnU-Net Extractor (CUNEX)-for full-thickness corneal segmentation of anterior segment optical coheren...

Extended Rice-Thomson analysis and atomistic simulations revealing grain boundary effects on fracture in refractory high-entropy alloys.

Understanding how grain boundaries mediate fracture remains a critical challenge in designing ductile, high-performance refractory alloys. Here, we ex...

Artificial intelligence for epiretinal membrane detection using ultrawidefield scanning laser ophthalmoscopy.

BACKGROUND: There is currently no validated artificial intelligence (AI) model for detecting epiretinal membrane (ERM) using ultrawidefield scanning l...

Parameter-Efficient Contrastive Language-Image Pre-training (CLIP) Adaptation for Few-Shot Anomaly Detection in Ultra-Widefield Fundus Images.

Fundus diseases are among the leading causes of visual impairment and blindness, many of which could be prevented through early intervention. Ultra-wi...

What Kind of Other Is AI? Symbolization, Desire, and Adolescent Development in the Age of Artificial Intelligence.

Artificial intelligence (AI) is becoming a new kind of other in the psychic lives of adolescents. From emotionally responsive chatbots to AI-enhanced ...

Efficient SqueezeViT: A lightweight vision transformer framework for chest X-ray image classification.

This work introduces SqueezeViT (Squeeze Vision Transformers), a compact yet effective architecture based on Vision Transformers (ViT) designed for ch...