Telemedicine, the use of telecommunication and information technology to deliver
healthcare remotely, has evolved beyond recognition since its inception in the 1970s …

Background: An increasing amount of people are globally affected by retinal diseases, such
as diabetes, vascular occlusions, maculopathy, alterations of systemic circulation, and …

Purpose The primary objective of this study was to develop and validate an AI algorithm as a
screening tool for the detection of retinopathy of prematurity (ROP). Participants Images …

Transferring and replicating predictive algorithms across healthcare systems constitutes a
unique yet crucial challenge that needs to be addressed to enable the widespread adoption …

Retinopathy of prematurity (ROP) is a severe condition affecting premature infants, leading
to abnormal retinal blood vessel growth, retinal detachment, and potential blindness. While …

Aim Code-free deep learning (CFDL) allows clinicians without coding expertise to build high-
quality artificial intelligence (AI) models without writing code. In this review, we …

Chatbot-based multimodal AI holds promise for collecting medical histories and diagnosing
ophthalmic diseases using textual and imaging data. This study developed and evaluated …

Objectives The purpose of this study was to utilize a no-code computer vision platform to
develop, train, and evaluate a model specifically designed for segmenting dental …

Background To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a
deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical …

Purpose To develop non-imaging machine-learning models using clinical data from the first
screening to predict the occurrence of retinopathy of prematurity (ROP). Design This …