Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques | Zendy

Felix Yu | Zendy; Gianluca Silva Croso | Zendy; Tae Soo Kim | Zendy; Ziang Song | Zendy; Felix Parker | Zendy; Gregory D. Hager | Zendy; Austin Reiter | Zendy; S. Swaroop Vedula | Zendy; Haider Ali | Zendy; Shameema Sikder | Zendy

Open Access

Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques

Author(s) -

Felix Yu,

Gianluca Silva Croso,

Tae Soo Kim,

Ziang Song,

Felix Parker,

Gregory D. Hager,

Austin Reiter,

S. Swaroop Vedula,

Haider Ali,

Shameema Sikder

Publication year - 2019

Publication title -

jama network open

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.278

H-Index - 39

ISSN - 2574-3805

DOI - 10.1001/jamanetworkopen.2019.1860

Subject(s) - convolutional neural network , artificial intelligence , deep learning , computer science , machine learning , recurrent neural network , competence (human resources) , cataract surgery , receiver operating characteristic , artificial neural network , medicine , surgery , psychology , social psychology

Key Points Question Are deep learning techniques sufficiently accurate to classify presegmented phases in videos of cataract surgery for subsequent automated skill assessment and feedback? Findings In this cross-sectional study including videos from a convenience sample of 100 cataract procedures, modeling time series of labels of instruments in use appeared to yield greater accuracy in classifying phases of cataract operations than modeling cross-sectional data on instrument labels, spatial video image features, spatiotemporal video image features, or spatiotemporal video image features with appended instrument labels. Meaning Time series models of instruments in use may serve to automate the identification of phases in cataract surgery, helping to develop efficient and effective surgical skill training tools in ophthalmology.

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