Ophthalmology

Quantification, radiomics and artificial intelligence in infection imaging: Current status and future directions in nuclear medicine.

Nuclear medicine infection imaging has traditionally relied on semantic visual interpretation supported by simple semi-quantitative indices. While effective, this paradigm is limited by observer dependence, restricted sensitivity to subtle or diffuse disease, and difficulty in standardising interpretation across centres. Advances in quantitative imaging, radiomics and artificial intelligence (AI) ...

Ferroptosis regulator NOX1 acts a diagnostic biomarker and mediates disease progression with the transcriptional regulation of STAT3 in glaucoma.

PURPOSE: Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness. Regrettably, the roles of ferroptosis-related (FR) genes in POAG remain elusive. DESIGN: Five GEO data sets and a series of experimentations in vitro were used for bioinformatic exploration and biological validation. METHODS: Using multiple machine learning algorithms, four critical FR genes in POAG progres...

DDFU-Net: A Deep Decoder-Focused U-Net Model for Retinal Lesion Segmentation.

Early detection of retinal lesions helps to avoid visual loss or blindness. The main lesions associated with eye diseases include soft exudates, hard ...

Application of a Large Visual Language Model on Tongue Image Description Generation and Physical Constitution Reasoning in Traditional Chinese Medicine (TongueVLM): Model Development and Validation Study.

BACKGROUND: In the field of traditional Chinese medicine (TCM), diagnostic work based on tongue images to recognize the physical constitution is a pro...

Toward Long-Term Visual Field Appearance Forecasting Using Artificial Intelligence for Ophthalmic Education and Diagnosis.

OBJECTIVE: To provide state-of-the-art, post hoc-explainable visual field (VF) forecasts to aid in training ophthalmic residents to characterize glauc...

Automatic deep learning-based segmentation of cornea and lens in 2D OCT images of rabbit eyes.

Anterior-segment optical coherence tomography (AS-OCT) supports cataract surgery planning by revealing corneal and crystalline lens geometry, but clin...

[Application of artificial intelligence in pathological diagnosis of ocular tumors].

Ocular tumors encompass ocular surface tumors, orbital tumors, and intraocular tumors, characterized by high heterogeneity and complex classifications...

Fly motion vision maximizes signal energy transfer between mechanical input and sensor output.

Insects achieve agile flight using a sensor-rich control architecture whose embodiment eliminates the need for complex computation. For example, their...

Robot-mediated haptic feedback outperforms vision in violin duo coordination.

Joint actions among humans rely on the integration of multiple sensory modalities, most notably auditory and visual cues, which support explicit commu...

OCT-based myopic index: a biological predictor for the progression of high myopia.

BACKGROUND: The growth of axial length (AL) can lead to high myopia and ocular deformation, especially causing microstructural changes in the fundus, ...

Frontal facial analysis of male celebrities attractiveness standards through artificial intelligence.

OBJECTIVES: The modern emphasis on celebrities' facial features highlights their increasing role in defining beauty ideals. This retrospective study u...

Bio-inspired small target detecting visual neural network with motion direction decoding compensation in large scene.

Small target moving detection in a wide field of view and complex background is an extremely challenging task due to the small number of target pixels...

A bio-inspired spiking neural network with adaptive spatiotemporal filtering and depth-modulated synaptic plasticity for robust collision detection.

Achieving fast and robust collision detection on autonomous agents requires perceiving threats and issuing early warnings with minimal latency. Partic...

Reply to Comment on "Artificial intelligence-guided end point selection for neuroprotection trials in glaucoma".

Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology.

PURPOSE: Standard supervised learning assumes deterministic labels (e.g., positive or negative, present or absent), neglecting the diagnostic uncertai...

A multimodal retinal image dataset for diabetic retinopathy detection using foundation models.

Diabetic Retinopathy (DR), a leading cause of preventable blindness worldwide, underscores the urgent need for robust AI-driven diagnostic tools. Alth...

SYN-OCT:A synthetic dataset of ocular optical coherence tomography images from healthy and glaucoma eyes.

The SYN-OCT dataset contains a total of 200,000 synthetic cross-sectional circumpapillary optical coherence tomography (OCT) images, comprising of 100...

A SEM-ANN analysis to examine impact of AI overreliance through a social cognitive lens: the roles of dependency, FOMO, addiction, and anxiety.

The rapid integration of artificial intelligence (AI) has transformed how people learn, work, and make decisions, while raising growing concerns about...

Use of synthetic data, a novel paradigm for immunopathology.

The complexity and heterogeneity of autoimmune diseases are only partially captured by current analytic tools, even when deep learning techniques are ...

Movie reconstruction from mouse visual cortex activity.

The ability to reconstruct images represented by the brain has the potential to give us an intuitive understanding of what the brain sees. Reconstruct...