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Smartphone app for non-invasive detection of anemia using only patient-sourced photos

We introduce a paradigm of completely non-invasive, on-demand diagnostics that may replace common blood-based laboratory tests using only a smartphone app and photos. We initially targeted anemia, a blood condition characterized by low blood hemoglobin levels that afflicts >2 billion people. Our...

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Autores principales: Mannino, Robert G., Myers, David R., Tyburski, Erika A., Caruso, Christina, Boudreaux, Jeanne, Leong, Traci, Clifford, G. D., Lam, Wilbur A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279826/
https://www.ncbi.nlm.nih.gov/pubmed/30514831
http://dx.doi.org/10.1038/s41467-018-07262-2
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author Mannino, Robert G.
Myers, David R.
Tyburski, Erika A.
Caruso, Christina
Boudreaux, Jeanne
Leong, Traci
Clifford, G. D.
Lam, Wilbur A.
author_facet Mannino, Robert G.
Myers, David R.
Tyburski, Erika A.
Caruso, Christina
Boudreaux, Jeanne
Leong, Traci
Clifford, G. D.
Lam, Wilbur A.
author_sort Mannino, Robert G.
collection PubMed
description We introduce a paradigm of completely non-invasive, on-demand diagnostics that may replace common blood-based laboratory tests using only a smartphone app and photos. We initially targeted anemia, a blood condition characterized by low blood hemoglobin levels that afflicts >2 billion people. Our app estimates hemoglobin levels by analyzing color and metadata of fingernail bed smartphone photos and detects anemia (hemoglobin levels <12.5 g dL(−1)) with an accuracy of ±2.4 g dL(−1) and a sensitivity of 97% (95% CI, 89–100%) when compared with CBC hemoglobin levels (n = 100 subjects), indicating its viability to serve as a non-invasive anemia screening tool. Moreover, with personalized calibration, this system achieves an accuracy of ±0.92 g dL(−1) of CBC hemoglobin levels (n = 16), empowering chronic anemia patients to serially monitor their hemoglobin levels instantaneously and remotely. Our on-demand system enables anyone with a smartphone to download an app and immediately detect anemia anywhere and anytime.
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spelling pubmed-62798262018-12-06 Smartphone app for non-invasive detection of anemia using only patient-sourced photos Mannino, Robert G. Myers, David R. Tyburski, Erika A. Caruso, Christina Boudreaux, Jeanne Leong, Traci Clifford, G. D. Lam, Wilbur A. Nat Commun Article We introduce a paradigm of completely non-invasive, on-demand diagnostics that may replace common blood-based laboratory tests using only a smartphone app and photos. We initially targeted anemia, a blood condition characterized by low blood hemoglobin levels that afflicts >2 billion people. Our app estimates hemoglobin levels by analyzing color and metadata of fingernail bed smartphone photos and detects anemia (hemoglobin levels <12.5 g dL(−1)) with an accuracy of ±2.4 g dL(−1) and a sensitivity of 97% (95% CI, 89–100%) when compared with CBC hemoglobin levels (n = 100 subjects), indicating its viability to serve as a non-invasive anemia screening tool. Moreover, with personalized calibration, this system achieves an accuracy of ±0.92 g dL(−1) of CBC hemoglobin levels (n = 16), empowering chronic anemia patients to serially monitor their hemoglobin levels instantaneously and remotely. Our on-demand system enables anyone with a smartphone to download an app and immediately detect anemia anywhere and anytime. Nature Publishing Group UK 2018-12-04 /pmc/articles/PMC6279826/ /pubmed/30514831 http://dx.doi.org/10.1038/s41467-018-07262-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mannino, Robert G.
Myers, David R.
Tyburski, Erika A.
Caruso, Christina
Boudreaux, Jeanne
Leong, Traci
Clifford, G. D.
Lam, Wilbur A.
Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title_full Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title_fullStr Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title_full_unstemmed Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title_short Smartphone app for non-invasive detection of anemia using only patient-sourced photos
title_sort smartphone app for non-invasive detection of anemia using only patient-sourced photos
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279826/
https://www.ncbi.nlm.nih.gov/pubmed/30514831
http://dx.doi.org/10.1038/s41467-018-07262-2
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