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Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders
Digital technologies—including smartphones, wearables, and social media data—show great potential for helping to alleviate suffering from brain disorders such as Parkinson’s disease, Alzheimer’s disease, depression, and schizophrenia. However, as researchers, technology developers, disease-focused g...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550158/ https://www.ncbi.nlm.nih.gov/pubmed/31304390 http://dx.doi.org/10.1038/s41746-019-0123-z |
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author | Stroud, Clare Onnela, Jukka-Pekka Manji, Husseini |
author_facet | Stroud, Clare Onnela, Jukka-Pekka Manji, Husseini |
author_sort | Stroud, Clare |
collection | PubMed |
description | Digital technologies—including smartphones, wearables, and social media data—show great potential for helping to alleviate suffering from brain disorders such as Parkinson’s disease, Alzheimer’s disease, depression, and schizophrenia. However, as researchers, technology developers, disease-focused groups, and others forge forward to take advantage of the tremendous opportunities in this domain, it is important to avoid hype and overpromising, and to ensure that this work is done rigorously and collaboratively. In June 2018, the National Academies of Sciences, Engineering, and Medicine’s Forum on Neuroscience and Nervous System Disorders hosted a workshop that brought together a wide range of experts and stakeholders. The workshop provided an opportunity to take stock of the rapidly-evolving landscape and discuss how to work together to address both scientific and practical challenges, so that the potential of digital technologies can be translated into meaningful contributions toward the health of individuals and society. Workshop presentations and discussions focused on four key challenges: transforming data into insight, navigating regulatory pathways, designing user-centered tools, and building partnerships across a complex ecosystem. This article highlights the many issues, challenges, and opportunities discussed by individual participants at the workshop. |
format | Online Article Text |
id | pubmed-6550158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65501582019-07-12 Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders Stroud, Clare Onnela, Jukka-Pekka Manji, Husseini NPJ Digit Med Perspective Digital technologies—including smartphones, wearables, and social media data—show great potential for helping to alleviate suffering from brain disorders such as Parkinson’s disease, Alzheimer’s disease, depression, and schizophrenia. However, as researchers, technology developers, disease-focused groups, and others forge forward to take advantage of the tremendous opportunities in this domain, it is important to avoid hype and overpromising, and to ensure that this work is done rigorously and collaboratively. In June 2018, the National Academies of Sciences, Engineering, and Medicine’s Forum on Neuroscience and Nervous System Disorders hosted a workshop that brought together a wide range of experts and stakeholders. The workshop provided an opportunity to take stock of the rapidly-evolving landscape and discuss how to work together to address both scientific and practical challenges, so that the potential of digital technologies can be translated into meaningful contributions toward the health of individuals and society. Workshop presentations and discussions focused on four key challenges: transforming data into insight, navigating regulatory pathways, designing user-centered tools, and building partnerships across a complex ecosystem. This article highlights the many issues, challenges, and opportunities discussed by individual participants at the workshop. Nature Publishing Group UK 2019-06-03 /pmc/articles/PMC6550158/ /pubmed/31304390 http://dx.doi.org/10.1038/s41746-019-0123-z Text en © The Author(s) 2019 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 | Perspective Stroud, Clare Onnela, Jukka-Pekka Manji, Husseini Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title | Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title_full | Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title_fullStr | Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title_full_unstemmed | Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title_short | Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
title_sort | harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550158/ https://www.ncbi.nlm.nih.gov/pubmed/31304390 http://dx.doi.org/10.1038/s41746-019-0123-z |
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