Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

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RPEGENE-Net: A Multi-Resolution Deep Learning Framework for Predicting Gene Expression from Microscopy Images of Retinal Pigment Epithelium (RPE) Cells

To develop a deep learning framework, RPEGENE-Net, capable of predicting gene expression profiles of retinal pigment epithelium (RPE) cells using live-cell microscopy images. A dataset of live-cell images of RPE cells, treated with various drug regimens and captured at magnifications of 40x, 100x, 200x, and 400x, was used. Gene expression of six key genes involved in epithelial-mesenchymal transit...

Artificial intelligence-enabled automated analysis of transmission electron micrographs to evaluate chemotherapy impact on mitochondrial morphology in triple negative breast cancer

Advancements in transmission electron microscopy (TEM) have enabled in-depth studies of biological specimens, offering new avenues to large-scale imaging experiments with subcellular resolution. Mitochondrial structure is of growing interest in cancer biology due to its crucial role in regulating the multi-faceted functions of mitochondria. We and others have established the crucial role of mitoch...

On-The-Fly Live-Cell Intrinsic Morphological Drug and Genetic Screens by Gigapixel-per-second Spinning Arrayed Disk Imaging

Next-generation drug discovery and functional genomics require rapid, unbiased single-cell profiling at scale—demands that exceed the limited speed, t...

Benchmarking resting state fMRI connectivity pipelines for classification: Robust accuracy despite processing variability in cross-site eye state prediction

The rapid evolution of machine learning (ML) methods has yielded promising results in human brain neuroscience. However, the reproducibility of ML app...

Computer Vision Methods for Spatial Transcriptomics: A Survey

Spatial transcriptomics (ST) enables the simultaneous measurement of gene expression and spatial localization within tissue sections, providing unprec...

Integrated analysis implicates novel insights of NMB into lactate metabolism and immune response prediction in primary glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...

End-to-end evaluation of white matter microstructure of the visual pathway in asymmetric glaucoma

Diffusion magnetic resonance imaging is a non-invasive neuroimaging technique that enables in vivo evaluation of white matter microstructure, providin...

Dual-Field Microvascular Segmentation: Hemodynamically-Consistent Attention Learning for Retinal Vasculature Mapping

Accurate retinal Microvascular segmentation demands a balanced combination of anatomical fidelity and hemodynamic relevance. However, existing methods...

CNValidatron: Accurate And Efficient Validation of PennCNV Calls Using Computer Vision

Large rare copy number variants (CNVs) are a main source of genetic variation in the genome and are important in both evolution and disease risk. CNVs...

A geometric shape regularity effect in the human brain

The perception and production of regular geometric shapes, a characteristic trait of human cultures since prehistory, has unknown neural mechanisms. B...

A study on edge devices for image classification of the Tasmanian devil (Sarcophilus harrisii) for vaccine delivery

A target-specific bait dispenser is required for oral bait vaccination of the endangered Tasmanian devil (Sarcophilus harrisii) against the deadly dev...

Computational Characterization of Decision Making During Trans-saccadic Visual Perception

When sampling visual information from the environment, humans execute fast sequential saccadic eye movements and yet preserve stability in their visua...

Neural signatures of associational cortex emerge in a goal-directed model of visual search

Animals actively engage with their environment to gather information, continuously shaping both their sensory input and behavior. Understanding this c...

Attcatvgg-Net: an Explainable Multioutput Deep Learning Framework for Cataract Stage Classification and Visual Acuity Regression using Multicolor Fundus Images

The purpose of this study is to develop and evaluate an attention-guided deep learning model using the multicolor imaging module of Spectralis Optical...

Biologically Inspired Deep Neural Network Models for Visual Emotion Processing

The perception of opportunities and threats in complex visual scenes represents one of the main functions of the human visual system. The underlying n...

Assessment of Visual Function in Mice Using Light/Dark Box and Multi-Feature Machine Learning

The light/dark box test can be used to assess visual function in rodents based on their spontaneous behavior in response to light. Commonly used assay...

Understanding cortical computation through the lens of joint-embedding predictive architectures

Tracking prey or recognizing a lurking predator is as crucial for survival as anticipating their actions. To guide behavior, the brain must extract in...

Predictive vision-language integration in the human visual cortex

Integrating linguistic and visual information is a core function of human cognition, yet how information from these two modalities interacts in the br...

Epithelial convergent extension as a tuning process

Self-tuning—the ability of disordered systems to develop desired collective behaviors by tuning internal couplings in response to feedback—has recentl...

Machine Learning Identifies Common Risk Variants and Implicates Abnormal Vision Physiology in ASD

Genomic technology advancements have facilitated associations between genetic variants and disease risk. Rare deleterious variants can independently i...

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