Ophthalmology

A Multimodal Multitask Artificial Intelligence Model for Orthokeratology Contact Lens Fitting: An Integrated Framework to Enhance Lens Centration and Myopia Control Effect.

PURPOSE: To develop a multimodal, multitask artificial intelligence (AI) model to classify postfitting corneal topography patterns and predict axial length (AL) growth, while simultaneously outputting optimal orthokeratology (ortho-K) lens parameters and the predicted probability of axial growth to support clinical decisions. DESIGN: A retrospective analysis. SUBJECTS: Clinical data and corneal to...

A Deep Learning Framework for Predicting Teprotumumab Treatment Response in Thyroid Eye Disease.

PURPOSE: To develop and evaluate a deep learning-based framework for quantifying thyroid eye disease (TED) severity before and after teprotumumab treatment, an insulin-like growth factor-1 receptor inhibitor, and to create a predictive model for forecasting individual patient responses to therapy. DESIGN: A retrospective cohort study was conducted at a single institution, utilizing an image-based ...

GDPooled transformer: glaucoma detection using pooled attention based transformer with attention mechanism.

Glaucoma is a common eye disease affecting several people worldwide. Blindness can be avoided with proper treatment and regular examination. Delayed d...

Diagnostic performance of AI-assisted intraoperative imaging for parathyroid identification: a systematic review.

BACKGROUND: Intra-operative identification of parathyroid glands might be technically challenging and is a major source of hypocalcemia and nerve inju...

Machine learning assisted masking of parasitic signals in Bragg coherent diffraction imaging.

Bragg coherent diffraction imaging (BCDI) is a lens-less technique capable of imaging the strain in a particle in the size range from 20 nm up to seve...

Integrated artificial intelligence and omics for prediction and monitoring of pre-eclampsia.

Pre-eclampsia is a difficult pregnancy condition that causes high blood pressure and can lead to health complications in both mother and newborn, resu...

Deep learning for early diagnosis of uveal melanoma: a systematic review and meta-analysis.

BACKGROUND: Uveal melanoma (UM) is a rare cancer with an estimated annual incidence of 6 incidences per million people. About half of UM patients deve...

Artificial Intelligence-Based Medical Devices for Diabetic Retinopathy Screening in the European Union.

BACKGROUND: Diabetic retinopathy (DR) remains a leading cause of preventable blindness, yet screening programs across Europe face persistent workforce...

Deep Learning-Based Eye Rubbing Detection Using Wrist-Based Wearable Devices to Enable Rigorous Study of Risk Factors for Ectasia Progression.

PURPOSE: To develop and validate an artificial intelligence (AI)-enabled eye rubbing detection tool using sensor data collected from wrist-based weara...

Correlative analysis between ocular surface features and carotid plaque : A multimodal machine learning framework.

BACKGROUND AND OBJECTIVE: The diagnosis of carotid plaques plays an important role in revealing cardiovascular and cerebrovascular diseases, thus attr...

Agri-vision Bangladesh: A multi-crop augmented image dataset for automated disease diagnosis in Bottle Gourd, Zucchini, Papaya, and Tomato.

This article introduces Agri-Vision Bangladesh, a comprehensive, augmented image dataset designed to advance automated disease diagnosis in four econo...

Pathology of peripheral neuroblastic tumors.

Neuroblastoma is the most prevalent extracranial solid tumor in pediatric age populations worldwide and the most common neoplastic disease diagnosed i...

Generic fitting models learn edge representations from prenatal retinal waves.

Orientation selectivity-the representation of oriented edges-is a hallmark of biological vision, shared across mammals, birds, and reptiles. However, ...

Foundation models for ophthalmic imaging.

Foundation models represent a new frontier in ophthalmic artificial intelligence, enabling learning of transferable features from large unlabelled ima...

A Novel Method for Hydrogen Permeation Detection Using Reflective Microscopy and Machine Learning.

Localized detection of hydrogen permeation in steel membranes is crucial for practical applications but remains challenging. We present a reflective m...

Early Outcomes of Intravitreal Aflibercept 8 mg in Eyes Previously Treated with Aflibercept 2 mg for Neovascular Age-Related Macular Degeneration with AI-Based Biomarker Quantification.

INTRODUCTION: To evaluate the early outcomes of aflibercept 8 mg (afl8) treatment in patients with neovascular age-related macular degeneration (nAMD)...

One-stop strabismus digital diagnosis via AI-integrated skin-like and wearable "Eyelectronics".

Strabismus, affecting ~4% of children, impairs vision and psychosocial health. However, clinical diagnosis requires multiple instruments and stepwise ...

Advancement of cataract classification with artificial intelligence using anterior segment optical coherence tomography images with self-supervised vision transformer.

PURPOSE: To evaluate the efficacy of a self-supervised learning Vision Transformer (ViT) for classification of the nucleus, cortex, and posterior caps...

Distilling structural knowledge from CNNs to vision transformers for data-efficient visual recognition.

Knowledge distillation (KD) is an effective strategy to transfer learned representations from a pre-trained teacher model to a smaller student model. ...

MIL-Adapter: Coupling multiple instance learning and vision-language adapters for few-shot slide-level classification.

Contrastive language-image pretraining has greatly enhanced visual representation learning and enabled zero-shot classification. Vision-language langu...