Non-melanoma skin cancer diagnosis: a comparison between dermoscopic and smartphone images by unified visual and sonification deep learning algorithms.

Journal: Journal of cancer research and clinical oncology
Published Date: Sep 21, 2021

Abstract

PURPOSE: Non-melanoma skin cancer (NMSC) is the most frequent keratinocyte-origin skin tumor. It is confirmed that dermoscopy of NMSC confers a diagnostic advantage as compared to visual face-to-face assessment. COVID-19 restrictions diagnostics by telemedicine photos, which are analogous to visual inspection, displaced part of in-person visits. This study evaluated by a dual convolutional neural network (CNN) performance metrics in dermoscopic (DI) versus smartphone-captured images (SI) and tested if artificial intelligence narrows the proclaimed gap in diagnostic accuracy.

Authors

  • A Dascalu
    Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. Electronic address: dasc@post.tau.ac.il.
  • B N Walker
    Sonification Lab, School of Psychology, School of Interactive Computing, Georgia Institute of Technology (Walker BN), Georgia.
  • Y Oron
    Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, 6 Matmon Cohen Street, 6209406, Tel Aviv, Israel.
  • E O David
    Department of Computer Science, Bar-Ilan University, Ramat-Gan, Israel.

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