Tracking Online Interest in Artificial Intelligence in Ophthalmology Using Google Trends.

Autor:	Ahuja AS; Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA., Rahimy E; Department of Ophthalmology, Palo Alto Medical Foundation, Palo Alto, CA, USA.; Byers Eye Institute, Stanford University School of Medicine, Palo Alto, CA, USA., Sridhar J; Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, FL, USA.
Jazyk:	angličtina
Zdroj:	Seminars in ophthalmology [Semin Ophthalmol] 2023 Oct; Vol. 38 (7), pp. 644-647. Date of Electronic Publication: 2023 Apr 24.
DOI:	10.1080/08820538.2023.2204919
Abstrakt:	Purpose: To examine trends in internet search queries related to artificial intelligence (AI) in ophthalmology and determine the correlation between online interest in AI, capital investment in AI, and peer-reviewed indexed publications regarding AI and ophthalmology. Methods: Online search trends for "AI retina", "AI eye", and "AI healthcare" were obtained via Google Trends from 2016 to 2022 on a relative interest scale in 1-week intervals. Global venture financing of AI- and machine learning (ML)-focused companies in healthcare was tracked from 2010 to 2019 from the consulting company, Klynveld Peat Marwick Goerdeler (KPMG), and the technology market intelligence company, CB Insights. Citation count from pubmed.gov was determined using the search query "artificial intelligence retina" from 2012 to 2021. Results: An increasingly linear growth in online search trends for "AI retina", "AI eye", and "AI healthcare" keyword searches was observed between 2016 and 2022. Global venture financing of AI and ML companies in healthcare also increased exponentially over the same time frame. There was an exponential increase in citations with nearly a 10-fold increase as reported by PubMed from 2015 onwards for the "artificial intelligence retina" search query. There was a significant and positive correlation between online search trends and investment trends (correlation coefficients of 0.98-0.99 and p -values <0.05) and between online search trends and citation count trends (correlation coefficients of 0.98-0.99 and p -values <0.05). Conclusions: These results demonstrate that the applications of AI and ML in ophthalmology are increasingly being investigated, financed, and formally researched, suggesting a prominent role for AI-derived tools in ophthalmology clinical practice in the near future.
Databáze:	MEDLINE
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