Ophthalmology

Neural network assisted annotation and analysis tool to study in-vivo foveolar cone photoreceptor topography.

The foveola, the central region of the human retina, plays a crucial role in sharp color vision and is challenging to study due to its unique anatomy and technical limitations in imaging. We present ConeMapper, an open-source MATLAB software that integrates a fully convolutional neural network (FCN) for the automatic detection and analysis of cone photoreceptors in confocal adaptive optics scannin...

Machine learning analysis of a Fano resonance based plasmonic refractive index sensor using U shaped resonators.

Plasmonic sensors have received special consideration for refractive index (RI) measurement due to the benefits of compact footprints and high sensitivities. To fulfill such conditions, a Fano resonance (FR)-based RI sensor using plasmonic nano-structures is designed and analyzed here. The presented topology comprises a metal-insulator-metal waveguide, a U-shaped, and an inverted U-shaped resonato...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium chloride has posed a significant challenge due to ...

A novel hybrid vision UNet architecture for brain tumor segmentation and classification.

This paper focuses on designing and developing novel architectures termed Hybrid Vision UNet-Encoder Decoder (HVU-ED) segmenter and Hybrid Vision UNet...

Multi-modal Classification of Retinal Disease Based On Convolutional Neural Network.

Retinal diseases such as age-related macular degeneration and diabetic retinopathy will lead to irreversible blindness without timely diagnosis and tr...

A three-tier AI solution for equitable glaucoma diagnosis across China's hierarchical healthcare system.

Artificial intelligence (AI) offers a solution to glaucoma care inequities driven by uneven resource distribution, but its real-world implementation r...

Preserving Professional Human Caring in Nursing in the Era of Artificial Intelligence.

This article examines Professional Human Caring in Nursing within the evolving landscape of artificial intelligence (AI). As AI becomes increasingly i...

Artificial Intelligence-Assisted Conductive Hydrogel Dressings for Refractory Wounds Monitoring.

Refractory wounds cause significant harm to the health of patients and the most common treatments in clinical practice are surgical debridement and wo...

Universal dimensions of visual representation.

Do visual neural networks learn brain-aligned representations because they share architectural constraints and task objectives with biological vision ...

Individualized structural network deviations predict surgical outcome in mesial temporal lobe epilepsy: a multicentre validation study.

BACKGROUND: Surgical resection is an effective treatment for medically refractory mesial temporal lobe epilepsy (mTLE), however, more than one-third o...

Stereotactic radiotherapy or protons for uveal melanoma patients? An artificial intelligence (AI)-based clinical treatment decision-making tool predicting doses to radiotherapy constraints.

PURPOSE: For ocular melanoma, selecting between stereotactic radiotherapy (SRT) and protons requires a lengthy plan comparison process. The purpose of...

Machine learning-driven prediction of eye irritation toxicity: Integration of in silico and in vitro study.

Eye irritation (EI) toxicity poses critical challenges in chemical safety assessment, demanding alternatives to ethically contentious animal testing. ...

Generative artificial intelligence for fundus fluorescein angiography interpretation and human expert evaluation.

Fundus fluorescein angiography (FFA) is the gold standard for diagnosing chorioretinal diseases, but its interpretation requires significant expertise...

WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification.

Weed detection and classification using computer vision and deep learning techniques have emerged as crucial tools for precision agriculture, offering...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its identification and categorization. This research used ...

Comparing IOL refraction prediction accuracy and A-constant optimization for cataract surgery patients across South Indian and Midwestern United States populations.

BACKGROUND: IOL power selection is a key determinant of refractive outcomes after cataract surgery. Numerous formulas exist to aid in this process; so...

Quantitative Mapping of Oxygen Affinity to Local Chemical Environments in Ti-Zr-Nb-Ta Alloys via Machine Learning.

Simultaneously enhancing strength and ductility is a longstanding challenge in materials science. Recent studies show that incorporating oxygen into T...

Orbital CT deep learning models in thyroid eye disease rival medical specialists' performance in optic neuropathy prediction in a quaternary referral center and revealed impact of the bony walls.

PURPOSE: To develop and evaluate orbital CT deep learning (DL) models in optic neuropathy (ON) prediction in patients diagnosed with thyroid eye disea...

Uncovering memorization effect in the presence of spurious correlations.

Machine learning models often rely on simple spurious features - patterns in training data that correlate with targets but are not causally related to...

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG.

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patien...