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The SVML algorithm was applied to 183 OCT volume pairs (17.934 B\u2010scans) in 30 patients. Four independent, diagnosis\u2010blinded retina specialists indicated whether wAMD activity was present between 100 pairs of consecutive OCT volumes (9800 B\u2010scans) in the remaining 40 patients for comparison with the SVML algorithm and a non\u2010complex baseline algorithm using only retinal thickness. The SVML algorithm was assessed using inter\u2010observer variability and receiver operating characteristic (ROC) analyses.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The retina specialists showed an average Cohen's <jats:italic>\u03ba<\/jats:italic> of 0.57\u00a0\u00b1\u00a00.13 (minimum: 0.41, maximum: 0.83). The average <jats:italic>\u03ba<\/jats:italic> between the proposed algorithm and the retina specialists was 0.62\u00a0\u00b1\u00a00.05 and 0.43\u00a0\u00b1\u00a00.14 between the baseline algorithm and the retina specialists. Using each of the four retina specialists as the reference, the proposed method showed a superior area under the ROC curve of 0.91\u00a0\u00b1\u00a00.03 compared to the ROC 0.81\u00a0\u00b1\u00a00.05 shown by the baseline algorithm.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The SVML algorithm was as effective as the retina specialists were in detecting activity in wAMD. Support vector machine learning (SVML) may be a useful monitoring tool in wAMD suited for small samples that yield sparse OCT data possibly derived from self\u2010measuring OCT\u2010robots.<\/jats:p><\/jats:sec>","DOI":"10.1111\/aos.14055","type":"journal-article","created":{"date-parts":[[2019,3,6]],"date-time":"2019-03-06T13:18:31Z","timestamp":1551878311000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Feasibility of support vector machine learning in age\u2010related macular degeneration using small sample yielding sparse optical coherence tomography data"],"prefix":"10.1111","volume":"97","author":[{"given":"Gwenol\u00e9","family":"Quellec","sequence":"first","affiliation":[{"name":"ARTORG Centre for Biomedical Engineering Research University of Bern Bern Switzerland"},{"name":"Inserm, UMR 1101 Brest France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jens","family":"Kowal","sequence":"additional","affiliation":[{"name":"ARTORG Centre for Biomedical Engineering Research University of Bern Bern Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal W.","family":"Hasler","sequence":"additional","affiliation":[{"name":"OCTlab Department of Ophthalmology University of Basel Basel Switzerland"},{"name":"Department of Ophthalmology University of Basel Basel Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hendrik P. 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