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This article was published in the following journal.
Name: JAMA ophthalmology
To develop a deep learning (DL) model for automated detection of glaucoma and to compare diagnostic capability against hand-craft features (HCFs) based on spectral domain optical coherence tomography ...
Biosignals like electrocardiogram or photoplethysmogram have been widely used for monitoring and determining status of patients. However, it has been recently discovered that more information than tha...
Deep learning has been recently introduced for soft sensors in industrial processes. However, most of the existing deep networks, such as stacked autoencoder, are pretrained in a layerwise unsupervise...
To compare the diagnostic performance of human gradings versus predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) dama...
Deep learning techniques have been increasingly used to provide more accurate and more accessible diagnosis of thorax diseases on chest radiographs. However, due to the lack of dense annotation of lar...
This study aims to investigate the feasibility and efficiency of CT radiomic analysis which serves as a high through-put analytical strategy applied to image big-data resource in evaluatin...
Panretinal photocoagulation reduces the risk of visual loss by 50% in patients with diabetic retinopathy. It is recognized that laser expansion into the retina may be associated with photo...
The intra-vitreous injection (IVT) of anti-VEGF (vascular endothelial growth factor) is currently the standard treatment for retinal neovascularization. The VEGF stimulates endothelial cel...
Artificial Intelligence and Machine Learning techniques may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in indi...
The object of this study is to investigate the damage to the retinal nerve fiber layer (RNFL) and ganglion cell complex layer (GCL+) in diabetic patients without retinal microangioma as de...
A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
Disease involving the common PERONEAL NERVE or its branches, the deep and superficial peroneal nerves. Lesions of the deep peroneal nerve are associated with PARALYSIS of dorsiflexion of the ankle and toes and loss of sensation from the web space between the first and second toe. Lesions of the superficial peroneal nerve result in weakness or paralysis of the peroneal muscles (which evert the foot) and loss of sensation over the dorsal and lateral surface of the leg. Traumatic injury to the common peroneal nerve near the head of the FIBULA is a relatively common cause of this condition. (From Joynt, Clinical Neurology, 1995, Ch51, p31)
Ophthalmology is the branch of medicine that is devoted to the study and treatment of eye diseases. As well as mild visual defects correctable by lenses, ophthalmology is concerned with glaucoma, uveitis and other serious conditions affecting the eye, ...