AIMC Topic: Slit Lamp Microscopy

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Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients.

Japanese journal of ophthalmology Dec 17, 2019
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
Slit Lamp Microscopy Low Tension Glaucoma Visual Fields Visual Field Tests Gonioscopy Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells Intraocular Pressure Male Disease Progression ROC Curve Area Under Curve Humans Young Adult Myopia Machine Learning Adult Diagnosis, Computer-Assisted Female Cross-Sectional Studies
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Universal artificial intelligence platform for collaborative management of cataracts.

The British journal of ophthalmology Sep 2, 2019
PURPOSE: To establish and validate a universal artificial intelligence (AI) platform for collaborative management of cataracts involving multilevel clinical scenarios and explored an AI-based medical referral pattern to improve collaborative efficien...
Vision Disorders Area Under Curve Cataract Extraction Cataract Slit Lamp Microscopy Intersectoral Collaboration Female Adolescent Aged ROC Curve Aged, 80 and over Mass Screening Adult Humans Male Artificial Intelligence Middle Aged
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Enhanced Tomographic Assessment to Detect Corneal Ectasia Based on Artificial Intelligence.

American journal of ophthalmology Aug 9, 2018
PURPOSE: To improve the detection of corneal ectasia susceptibility using tomographic data.
Keratomileusis, Laser In Situ Dilatation, Pathologic Female Tomography Cornea Humans Middle Aged Adult Corneal Pachymetry Male Artificial Intelligence Sensitivity and Specificity Slit Lamp Microscopy Keratoconus Retrospective Studies Case-Control Studies Corneal Topography ROC Curve Diagnostic Techniques, Ophthalmological
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Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.

The Lancet. Digital health Feb 1, 2021
BACKGROUND: Ocular changes are traditionally associated with only a few hepatobiliary diseases. These changes are non-specific and have a low detection rate, limiting their potential use as clinically independent diagnostic features. Therefore, we ai...
Area Under Curve Conjunctiva Fundus Oculi ROC Curve Mass Screening Liver Eye Digestive System Diseases Slit Lamp Microscopy Sclera Models, Biological Prospective Studies Iris Humans Photography Computer Simulation Middle Aged Algorithms Deep Learning Adult China
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Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

JAMA ophthalmology Apr 1, 2020
IMPORTANCE: Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.
Intraocular Pressure Male Middle Aged Aged, 80 and over Adult Cross-Sectional Studies Nerve Fibers Retinal Ganglion Cells Visual Fields Deep Learning ROC Curve Tomography, Optical Coherence Humans Slit Lamp Microscopy Algorithms Female Visual Field Tests Aged Glaucoma, Open-Angle Gonioscopy
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