Computer methods and programs in biomedicine
33765481
BACKGROUND AND OBJECTIVE: Previous studies developed artificial intelligence (AI) diagnostic systems only using eligible slit-lamp images for detecting corneal diseases. However, images of ineligible quality (including poor-field, defocused, and poor...
There is currently no objective portable screening modality for narrow angles in the community. In this prospective, single-centre image validation study, we used machine learning on slit lamp images taken with a portable smartphone device (MIDAS) to...
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophtha...
PURPOSE: The aim of this study was to facilitate deep learning systems in image annotations for diagnosing keratitis type by developing an automated algorithm to classify slit-lamp photographs (SLPs) based on illumination technique.
Allergology international : official journal of the Japanese Society of Allergology
39155213
BACKGROUND: Artificial intelligence (AI) is a promising new technology that has the potential of diagnosing allergic conjunctival diseases (ACDs). However, its development is slowed by the absence of a tailored image database and explainable AI model...