AI Medical Compendium Topic

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Glaucoma

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Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters.

PloS one
PURPOSE: This study aimed to develop a machine learning-based algorithm for objective classification of the optic disc in patients with open-angle glaucoma (OAG), using quantitative parameters obtained from ophthalmic examination instruments.

A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.

Journal of medical systems
This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundary detection of optic disc and cup to aid automatic glaucoma diagnosis. The novelty of our approach consists of two aspects: 1) automatic detection of ...

Development of machine learning models for diagnosis of glaucoma.

PloS one
The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features fro...

A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes.

Medical image analysis
Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Meas...

Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy sampling technique is used to select informative points thus reducing computational complexity while perfor...

A Hybrid Swarm Algorithm for optimizing glaucoma diagnosis.

Computers in biology and medicine
Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist early diagnosis in the vast population. Such mass screening requires an automated diagnosis technique....

Ethics of Artificial Intelligence in Medicine and Ophthalmology.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
BACKGROUND: This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first introduced in the 1950s, is defined as "the machine simulation of human mental reasoning, decision ma...

Interpreting Deep Learning Studies in Glaucoma: Unresolved Challenges.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Deep learning algorithms as tools for automated image classification have recently experienced rapid growth in imaging-dependent medical specialties, including ophthalmology. However, only a few algorithms tailored to specific health conditions have ...

High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

Translational vision science & technology
PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis and management. The ability to accurately digitize VF reports is critical for maximizing the utility...