AIMC Topic: Intraocular Pressure
Clear Filters Showing 21 to 30 of 122 articles
Remote and low-cost intraocular pressure monitoring by deep learning of speckle patterns.
Journal of biomedical optics
Mar 29, 2024
SIGNIFICANCE: Glaucoma, a leading cause of global blindness, disproportionately affects low-income regions due to expensive diagnostic methods. Affordable intraocular pressure (IOP) measurement is crucial for early detection, especially in low- and m...
Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data.
Indian journal of ophthalmology
Mar 8, 2024
OBJECTIVE: To develop machine learning (ML) models, using pre and intraoperative surgical parameters, for predicting trabeculectomy outcomes in the eyes of patients with juvenile-onset primary open-angle glaucoma (JOAG) undergoing primary surgery.
Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.
American journal of ophthalmology
Feb 12, 2024
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...
Intraocular Pressure
Male
Middle Aged
Disease Progression
Retrospective Studies
Female
Aged
Area Under Curve
Tomography, Optical Coherence
Nerve Fibers
Optic Disk
Deep Learning
ROC Curve
Follow-Up Studies
Vision Disorders
Humans
Glaucoma
Algorithms
Optic Nerve Diseases
Glaucoma, Open-Angle
Retinal Ganglion Cells
Visual Fields
Visual Field Tests
Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability.
Ophthalmology. Glaucoma
Jan 29, 2024
PURPOSE: Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and study the impact of using this DLM on sample size requirements for neuroprotective trials.
Prediction and Detection of Glaucomatous Visual Field Progression Using Deep Learning on Macular Optical Coherence Tomography.
Journal of glaucoma
Jan 12, 2024
PRCIS: A deep learning model trained on macular OCT imaging studies detected clinically significant functional glaucoma progression and was also able to predict future progression.
Predicting 60-4 visual field tests using 3D facial reconstruction.
The British journal of ophthalmology
Dec 18, 2023
BACKGROUND: Despite, the potential clinical utility of 60-4 visual fields, they are not frequently used in clinical practice partly, due to the purported impact of facial contour on field defects. The purpose of this study was to design and test an a...
Predicting glaucoma progression using deep learning framework guided by generative algorithm.
Scientific reports
Nov 15, 2023
Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomog...
Assessment of angle closure disease in the age of artificial intelligence: A review.
Progress in retinal and eye research
Nov 3, 2023
Primary angle closure glaucoma is a visually debilitating disease that is under-detected worldwide. Many of the challenges in managing primary angle closure disease (PACD) are related to the lack of convenient and precise tools for clinic-based disea...
Deep learning visual field global index prediction with optical coherence tomography parameters in glaucoma patients.
Scientific reports
Oct 25, 2023
The aim of this study was to predict three visual filed (VF) global indexes, mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI), from optical coherence tomography (OCT) parameters including Bruch's Membrane Opening-Mi...
Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements.
American journal of ophthalmology
Sep 19, 2023
PURPOSE: To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements.
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823