Open AccessBig Data in Ophthalmology
Author(s) -
Ching-Yu Cheng,
Zhi Da Soh,
Shivani Majithia,
Sahil Thakur,
Tyler Hyungtaek Rim,
Yih Chung Tham,
Tien Yin Wong
Publication year - 2020
Publication title -
asia-pacific journal of ophthalmology
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.163
H-Index - 20
ISSN - 2162-0989
DOI - 10.1097/apo.0000000000000304
Subject(s) - big data , biobank , data science , social media , quality (philosophy) , work (physics) , computer science , engineering , data mining , world wide web , mechanical engineering , philosophy , epistemology , biology , genetics
Big data is the fuel of mankind's fourth industrial revolution. Coupled with new technology such as artificial intelligence and deep learning, the potential of big data is poised to be harnessed to its maximal in years to come. In ophthalmology, given the data-intensive nature of this specialty, big data will similarly play an important role. Electronic medical records, administrative and health insurance databases, mega national biobanks, crowd source data from mobile applications and social media, and international epidemiology consortia are emerging forms of "big data" in ophthalmology. In this review, we discuss the characteristics of big data, its potential applications in ophthalmology, and the challenges in leveraging and using these data. Importantly, in the next phase of work, it will be pertinent to further translate "big data" findings into real-world applications, to improve quality of eye care, and cost-effectiveness and efficiency of health services in ophthalmology.