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Addressing Medicine’s Dark Matter

In the 20th century, the models used to predict the motion of heavenly bodies did not match observation. Investigating this incongruity led to the discovery of dark matter—the most abundant substance in the universe. In medicine, despite years of using a data-hungry approach, our models have been li...

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Detalles Bibliográficos
Autores principales: Rose, Christian, Díaz, Mark, Díaz, Tomás
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434397/
https://www.ncbi.nlm.nih.gov/pubmed/35976194
http://dx.doi.org/10.2196/37584
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author Rose, Christian
Díaz, Mark
Díaz, Tomás
author_facet Rose, Christian
Díaz, Mark
Díaz, Tomás
author_sort Rose, Christian
collection PubMed
description In the 20th century, the models used to predict the motion of heavenly bodies did not match observation. Investigating this incongruity led to the discovery of dark matter—the most abundant substance in the universe. In medicine, despite years of using a data-hungry approach, our models have been limited in their ability to predict population health outcomes—that is, our observations also do not meet our expectations. We believe this phenomenon represents medicine’s “dark matter”— the features which have a tremendous effect on clinical outcomes that we cannot directly observe yet. Advancing the information science of health care systems will thus require unique solutions and a humble approach that acknowledges its limitations. Dark matter changed the way the scientific community understood the universe; what might medicine learn from what it cannot yet see?
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spelling pubmed-94343972022-09-02 Addressing Medicine’s Dark Matter Rose, Christian Díaz, Mark Díaz, Tomás Interact J Med Res Viewpoint In the 20th century, the models used to predict the motion of heavenly bodies did not match observation. Investigating this incongruity led to the discovery of dark matter—the most abundant substance in the universe. In medicine, despite years of using a data-hungry approach, our models have been limited in their ability to predict population health outcomes—that is, our observations also do not meet our expectations. We believe this phenomenon represents medicine’s “dark matter”— the features which have a tremendous effect on clinical outcomes that we cannot directly observe yet. Advancing the information science of health care systems will thus require unique solutions and a humble approach that acknowledges its limitations. Dark matter changed the way the scientific community understood the universe; what might medicine learn from what it cannot yet see? JMIR Publications 2022-08-17 /pmc/articles/PMC9434397/ /pubmed/35976194 http://dx.doi.org/10.2196/37584 Text en ©Christian Rose, Mark Díaz, Tomás Díaz. Originally published in the Interactive Journal of Medical Research (https://www.i-jmr.org/), 17.08.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Interactive Journal of Medical Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.i-jmr.org/, as well as this copyright and license information must be included.
spellingShingle Viewpoint
Rose, Christian
Díaz, Mark
Díaz, Tomás
Addressing Medicine’s Dark Matter
title Addressing Medicine’s Dark Matter
title_full Addressing Medicine’s Dark Matter
title_fullStr Addressing Medicine’s Dark Matter
title_full_unstemmed Addressing Medicine’s Dark Matter
title_short Addressing Medicine’s Dark Matter
title_sort addressing medicine’s dark matter
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434397/
https://www.ncbi.nlm.nih.gov/pubmed/35976194
http://dx.doi.org/10.2196/37584
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