Health data that are publicly available are valuable resources for digital health research. Several public datasets containing ophthalmological imaging have been frequently used in machine learning research; however, the total number of datasets containing ophthalmological health information and their respective content is unclear. This Review aimed to identify all publicly available ophthalmological imaging datasets, detail their accessibility, describe which diseases and populations are represented, and report on the completeness of the associated metadata. With the use of MEDLINE, Google's search engine, and Google Dataset Search, we identified 94 open access datasets containing 507 724 images and 125 videos from 122 364 patients. Most datasets originated from Asia, North America, and Europe. Disease populations were unevenly represented, with glaucoma, diabetic retinopathy, and age-related macular degeneration disproportionately overrepresented in comparison with other eye diseases. The reporting of basic demographic characteristics such as age, sex, and ethnicity was poor, even at the aggregate level. This Review provides greater visibility for ophthalmological datasets that are publicly available as powerful resources for research. Our paper also exposes an increasing divide in the representation of different population and disease groups in health data repositories. The improved reporting of metadata would enable researchers to access the most appropriate datasets for their needs and maximise the potential of such resources.

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This review aims to consolidate the available information on use of electroretinography as a diagnostic tool in psychiatry. The electroretinogram (ERG) has been found to have diagnostic utility in cocaine withdrawal (reduced light-adapted b-wave response), major depressive disorder (reduced contrast gain in pattern ERG), and schizophrenia (reduced a- and b-wave amplitudes). This review examines these findings as well as the applicability of ERG to substance use disorder, Alzheimer’s disease, autism spectrum disorder, panic disorder, eating disorders, attention deficit hyperactivity disorder, and medication use. While there have been promising results, current research suffers from a lack of specificity. Further research that quantifies anomalies in ERG present in psychiatric illness is needed.