ABSTRACT BACKGROUND: Artificial intelligence (AI) deals with development of algorithms that seek to perceive one’s environment and perform actions that maximize one’s chance of successfully reaching one’s predetermined goals. OBJECTIVE: To provide an overview of the basic principles of AI and its main studies in the fields of glaucoma, retinopathy of prematurity, age-related macular degeneration and diabetic retinopathy. From this perspective, the limitations and potential challenges that have accompanied the implementation and development of this new technology within ophthalmology are presented. DESIGN AND SETTING: Narrative review developed by a research group at the Universidade Federal de São Paulo (UNIFESP), São Paulo (SP), Brazil. METHODS: We searched the literature on the main applications of AI within ophthalmology, using the keywords “artificial intelligence”, “diabetic retinopathy”, “macular degeneration age-related”, “glaucoma” and “retinopathy of prematurity,” covering the period from January 1, 2007, to May 3, 2021. We used the MEDLINE database (via PubMed) and the LILACS database (via Virtual Health Library) to identify relevant articles. RESULTS: We retrieved 457 references, of which 47 were considered eligible for intensive review and critical analysis. CONCLUSION: Use of technology, as embodied in AI algorithms, is a way of providing an increasingly accurate service and enhancing scientific research. This forms a source of complement and innovation in relation to the daily skills of ophthalmologists. Thus, AI adds technology to human expertise.

ABSTRACT Objective To analyze the most common ophthalmologic disorders in pregnant women seen in a hospital in Munich in Germany using a big data analysis system, as well as to compare the results obtained with those from other epidemiological studies that used different data acquisition methods. Methods We retrospectively analyzed electronic health records of pregnant women who were seen at the ophthalmology department from 2003 to 2019 at the Ludwig-Maximilians-Universität München hospital. The main complaints that led to ophthalmic consultations during this period were evaluated, and also the variation in intraocular pressure of patients throughout gestational trimesters by analyzing data from the data warehouse system. Results A total of 27,326 electronic health records were analyzed. Of participants, 149 (0.54%) required eye care during pregnancy. Their mean intraocular pressure was 17mmHg in the first trimester, 12mmHg in the second trimester, and 14mmHg in the third trimester. The most prevalent findings were dry eye (29.3%) and conjunctivitis (16%), and ametropia (16%). The most common posterior segment problem was diabetic retinopathy (4.6%). The lower mean intraocular pressure in the second and third trimester found in our study is in accordance with other studies that used other method for data acquisition. Conclusion The most common ophthalmic conditions found in this study population were dry eye, conjunctivitis, and ametropia. The use of data warehouse proved to be useful for acquiring and analyzing data from many patients. This study results are comparable with other studies in published literature that adopted different methodology.