Mathematical biosciences and engineering : MBE
Mar 2, 2021
Content-based image analysis and computer vision techniques are used in various health-care systems to detect the diseases. The abnormalities in a human eye are detected through fundus images captured through a fundus camera. Among eye diseases, glau...
PURPOSE OF REVIEW: The field of artificial intelligence has grown exponentially in recent years with new technology, methods, and applications emerging at a rapid rate. Many of these advancements have been used to improve the diagnosis and management...
PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improve disease knowledge. Given COVID-19's effect on clinical practice, TR can maintain social distancing...
Journal of the Chinese Medical Association : JCMA
Nov 1, 2020
Artificial intelligence (AI), Internet of Things (IoT), and telemedicine are deeply involved in our daily life and have also been extensively applied in the medical field, especially in ophthalmology. Clinical ophthalmologists are required to perform...
BACKGROUND: Glaucoma is the most frequent cause of irreversible blindness worldwide. There is no cure, but early detection and treatment can slow the progression and prevent loss of vision. It has been suggested that artificial intelligence (AI) has ...
UNLABELLED: PRéCIS:: A spectral-domain optical coherence tomography (SD-OCT) based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminatin...
PURPOSE OF REVIEW: Current recommendations for glaucoma screening are decidedly neutral. No studies have yet documented improved long-term outcomes for individuals who undergo glaucoma screening versus those who do not. Given the long duration that w...
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.