Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Detecting Keratoconus Using Convolutional Neural Network on Smartphone

Version 1 : Received: 9 April 2020 / Approved: 16 April 2020 / Online: 16 April 2020 (12:38:42 CEST)

How to cite: Rostami, S. Detecting Keratoconus Using Convolutional Neural Network on Smartphone. Preprints 2020, 2020040271 (doi: 10.20944/preprints202004.0271.v1). Rostami, S. Detecting Keratoconus Using Convolutional Neural Network on Smartphone. Preprints 2020, 2020040271 (doi: 10.20944/preprints202004.0271.v1).

Abstract

Nowadays smartphone utilization for disease diagnosis and remote health care applications has become promising due to their ubiquity. Here, a novel convolutional neural network method for detecting keratoconus that is wholly implemented on a smartphone is proposed. The proposed method provides accurate detection of over 72.9% for all stages of keratoconus. Preliminary results indicate 90%, 83%, 64% and 52% detection rate for severe, advanced, moderate and mild stages of disease, respectively.

Subject Areas

Keratoconus; smartphone; cornea; convolutional neural network

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