1. Bringing Deep Learning Models to the Data: An Application in Recognizing Intra-Retinal Fluid on Optical Coherence Tomography (OCT) Images

    Bringing Deep Learning Models to the Data: An Application in Recognizing Intra-Retinal Fluid on Optical Coherence Tomography (OCT) Images

    Purpose : Amidst intense interest in deep learning in medicine, concerns regarding data privacy, security, and sharing are of increasing importance. A model-to-data approach, in which the model itself is transferred rather than data, can circumvent many of these challenges, but has not been previously tested in ophthalmology. The objective of our study was to determine whether a model-to-data deep learning approach (i.e. validation of the algorithm without any data transfer) can be successfully applied for the first time to deep learning in ophthalmology. Methods : This is a cross sectional study in which a deep learning algorithm model developed at ...

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