43
views
0
recommends
+1 Recommend
1 collections
    1
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Fundus image analysis through a self-learning machine: Computer determines risk factors in hypertension

      *

      Karger Kompass Ophthalmologie

      S. Karger AG

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be difficult because of the wide variety of features, patterns, colours, values and shapes that are present in real data. Here, we show that deep learning can extract new knowledge from retinal fundus images. Using deep-learning models trained on data from 284,335 patients and validated on two independent datasets of 12,026 and 999 patients, we predicted cardiovascular risk factors not previously thought to be present or quantifiable in retinal images, such as age (mean absolute error within 3.26 years), gender (area under the receiver operating characteristic curve (AUC) = 0.97), smoking status (AUC = 0.71), systolic blood pressure (mean absolute error within 11.23 mmHg) and major adverse cardiac events (AUC = 0.70). We also show that the trained deep-learning models used anatomical features, such as the optic disc or blood vessels, to generate each prediction.

          Related collections

          Most cited references 1

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          Deep Learning for Predicting Refractive Error From Retinal Fundus Images

          We evaluate how deep learning can be applied to extract novel information such as refractive error from retinal fundus imaging.
            Bookmark

            Author and article information

            Journal
            KOP
            10.1159/issn.2297-0118
            Karger Kompass Ophthalmologie
            S. Karger AG
            2297-0118
            2297-0045
            2020
            October 2020
            29 September 2020
            : 6
            : Suppl 1
            : 30-31
            Affiliations
            Klinik für Augenheilkunde, Experimentelle Ophthalmologie, Charité – Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
            Author notes
            *Prof. Dr. Olaf Strauß, Klinik für Augenheilkunde, Experimentelle Ophthalmologie, Charité – Universitätsmedizin Berlin, Campus Virchow-Klinikum, Augustenburger Platz 1, 15333 Berlin, Germany, olaf.strauss@charite.de
            Article
            511378 Kompass Ophthalmol 2020;6(suppl 1):30–31
            10.1159/000511378
            © 2020 S. Karger GmbH, Freiburg

            Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

            Page count
            Pages: 2
            Categories
            Knowledge Transfer

            Vision sciences, Ophthalmology & Optometry, Pathology

            Comments

            Comment on this article