Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based platforms (Google Vertex and Amazon Rekognition), and two distinct datasets. Two publicly available datasets, Messidor-2 and BRSET, were utilized for model development. The Messidor-2 consists of fundus photographs from diabetic patients and the BRSET is a multi-label dataset.

Performance of ChatGPT-4 in answering questions from the Brazilian National Examination for Medical Degree Revalidation.

Objective: The aim of this study was to evaluate the performance of ChatGPT-4.0 in answering the 2022 Brazilian National Examination for Medical Degree Revalidation (Revalida) and as a tool to provide feedback on the quality of the examination.

Methods: A total of two independent physicians entered all examination questions into ChatGPT-4.

Artificial intelligence for telemedicine diabetic retinopathy screening: a review.

Purpose: This study aims to compare artificial intelligence (AI) systems applied in diabetic retinopathy (DR) teleophthalmology screening, currently deployed systems, fairness initiatives and the challenges for implementation.

Methods: The review included articles retrieved from PubMed/Medline/EMBASE literature search strategy regarding telemedicine, DR and AI. The screening criteria included human articles in English, Portuguese or Spanish and related to telemedicine and AI for DR screening.

Fairness and generalizability of OCT normative databases: a comparative analysis.

Purpose: In supervised Machine Learning algorithms, labels and reports are important in model development. To provide a normality assessment, the OCT has an in-built normative database that provides a color base scale from the measurement database comparison. This article aims to evaluate and compare normative databases of different OCT machines, analyzing patient demographic, contrast inclusion and exclusion criteria, diversity index, and statistical approach to assess their fairness and generalizability.

Fairness and generalisability in deep learning of retinopathy of prematurity screening algorithms: a literature review.

Background: Retinopathy of prematurity (ROP) is a vasoproliferative disease responsible for more than 30 000 blind children worldwide. Its diagnosis and treatment are challenging due to the lack of specialists, divergent diagnostic concordance and variation in classification standards. While artificial intelligence (AI) can address the shortage of professionals and provide more cost-effective management, its development needs fairness, generalisability and bias controls prior to deployment to avoid producing harmful unpredictable results.

Sociodemographic disparities in ophthalmological clinical trials.

Introduction: In ophthalmology, clinical trials (CTs) guide the treatment of diseases such as diabetic retinopathy, myopia, age-related macular degeneration, glaucoma and keratoconus with distinct presentations, pathological characteristics and responses to treatment in minority populations.Reporting gender and race and ethnicity in healthcare studies is currently recommended by National Institutes of Health (NIH) and Food and Drug Administration (FDA) guidelines to ensure representativeness and generalisability; however, CT results that include this information have been limited in the past 30 years.The objective of this review is to analyse the sociodemographic disparities in ophthalmological phases III and IV CT based on publicly available data.

Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening.

Aims: This study aims to compare the performance of a handheld fundus camera (Eyer) and standard tabletop fundus cameras (Visucam 500, Visucam 540, and Canon CR-2) for diabetic retinopathy and diabetic macular edema screening.

Methods: This was a multicenter, cross-sectional study that included images from 327 individuals with diabetes. The participants underwent pharmacological mydriasis and fundus photography in two fields (macula and optic disk centered) with both strategies.

Optical Coherence Tomography Angiographic Evaluation of Macular Vessel Density in Diabetic Macular Edema After Intravitreal Dexamethasone Implants: A Prospective Interventional Trial.

Background And Objective: The goal of this study was to assess macular vascular density evolution, macular thickness, and functional outcomes after intravitreal dexamethasone implants for diabetic macular edema.

Patients And Methods: Vascular density was evaluated with optical coherence tomography (OCT) angiography in 21 eyes. Macular thickness was evaluated with structural OCT.

An emergency room influx and trauma cases prediction in a Brazilian ophthalmological hospital by an ophthalmologist without code experience.

Purpose: The emergency medical service is a fundamental part of healthcare, albeit crowded emergency rooms lead to delayed and low-quality assistance in actual urgent cases. Machine-learning algorithms can provide a smart and effective estimation of emergency patients' volume, which was previously restricted to artificial intelligence (AI) experts in coding and computer science but is now feasible by anyone without any coding experience through auto machine learning. This study aimed to create a machine-learning model designed by an ophthalmologist without any coding experience using AutoML to predict the influx in the emergency department and trauma cases.

Impact of SARS-CoV-2 pandemic on ophthalmological emergency visits: 1 year of experience.

Purpose: The COVID-19 pandemic began in March 2020 and changed the healthcare system overall. The pandemic led to resource allocation changes, overloading of intensive care units, apprehensiveness of patients to seek medical care not related to COVID-19, and an abrupt reduction in all nonurgent consultations and surgeries. This study evaluated the impact on an ophthalmological emergency room for one year by assessing the correlation between societal lockdown phases and COVID-19 mortality.

Diabetic retinopathy classification for supervised machine learning algorithms.

Background: Artificial intelligence and automated technology were first reported more than 70 years ago and nowadays provide unprecedented diagnostic accuracy, screening capacity, risk stratification, and workflow optimization. Diabetic retinopathy is an important cause of preventable blindness worldwide, and artificial intelligence technology provides precocious diagnosis, monitoring, and guide treatment. High-quality exams are fundamental in supervised artificial intelligence algorithms, but the lack of ground truth standards in retinal exams datasets is a problem.

Obstructive sleep apnea and the retina: a review.

Citation: This review's objective was to synthesize the literature on the repercussions of obstructive sleep apnea (OSA) in the retinal vascular system. Two independent investigators conducted a search using the MEDLINE/PubMed database using the following terms: sleep apnea syndrome, obstructive sleep apnea, retina, vascular tortuosity, central serous chorioretinopathy, diabetes mellitus, and subfoveal choroidal thickness. Patients with OSA present increased vascular tortuosity compared with patients without OSA, decreased parafoveal and peripapillary vessel density, and increased retinal vein occlusion incidence.

New Insights in Resistant Diabetic Macular Edema.

Diabetic macular edema (DME) is the most common cause of vision loss in diabetic eyes, and due to the rapid rise in the number of diabetic patients, the treatment burden has increased exponentially. The introduction of antivascular endothelial growth factor (anti-VEGF) therapy has been a major breakthrough in the management of center-involving DME, replacing laser photocoagulation as the first-line treatment. Despite the improvement in DME treatment with anti-VEGF therapy, persistent DME remains a challenge due to the extremely complex pathogenesis and the involvement of several different biochemical pathways.

Repeatability and Reproducibility of Photoreceptor Density Measurement in the Macula Using the Spectralis High Magnification Module.

Purpose: To evaluate the repeatability and reproducibility of photoreceptor density assessment with manual cell counting in healthy participants imaged with the Heidelberg Spectralis High Magnification Module (HMM).

Design: Precision study, evaluation of diagnostic test or technology.

Participants: Eleven eyes of 8 participants.

Centration in refractive surgery.

The point of centration for refractive surgery is a theme of great importance that generates considerable discussion among specialists and surgeons in the field. Notably, any changes in light can alter the size of the pupil, and the visual axis of the fixation line to the fovea is unique in each patient. A variety of options have been described in the literature with respect to centration in refractive surgery, and the results differ among these methods.

Quality-of-Life and Psychosocial Aspects in Patients with Ocular Toxoplasmosis: A Clinical Study in a Tertiary Care Hospital in Brazil.

To evaluate quality of life in patients with uveitis-related to toxoplasmosis and its correlation with demographic, ocular involvement and psychosocial aspects.: Data were collected through standardized interviews using a form to collect clinical and demographic data, in addition forms such as HADS, SF-12, NEI-VFQ-25 for health-related quality of life and anxiety and depression symptoms.: 81 patients were included with a mean age of 41.