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Biomedical informatics applications for precision management of neurodegenerative diseases
Modern medicine is in the midst of a revolution driven by “big data,” rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cogn...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6118097/ https://www.ncbi.nlm.nih.gov/pubmed/30175230 http://dx.doi.org/10.1016/j.trci.2018.03.007 |
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author | Miller, Justin B. Shan, Guogen Lombardo, Joseph Jimenez-Maggoria, Gustavo |
author_facet | Miller, Justin B. Shan, Guogen Lombardo, Joseph Jimenez-Maggoria, Gustavo |
author_sort | Miller, Justin B. |
collection | PubMed |
description | Modern medicine is in the midst of a revolution driven by “big data,” rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine. |
format | Online Article Text |
id | pubmed-6118097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61180972018-08-31 Biomedical informatics applications for precision management of neurodegenerative diseases Miller, Justin B. Shan, Guogen Lombardo, Joseph Jimenez-Maggoria, Gustavo Alzheimers Dement (N Y) Special Issue from the Centers of Biomedical Research Excellence (COBRE) and Center for Neurodegeneration and Translational Neuroscience (CNTN) Modern medicine is in the midst of a revolution driven by “big data,” rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine. Elsevier 2018-06-13 /pmc/articles/PMC6118097/ /pubmed/30175230 http://dx.doi.org/10.1016/j.trci.2018.03.007 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Special Issue from the Centers of Biomedical Research Excellence (COBRE) and Center for Neurodegeneration and Translational Neuroscience (CNTN) Miller, Justin B. Shan, Guogen Lombardo, Joseph Jimenez-Maggoria, Gustavo Biomedical informatics applications for precision management of neurodegenerative diseases |
title | Biomedical informatics applications for precision management of neurodegenerative diseases |
title_full | Biomedical informatics applications for precision management of neurodegenerative diseases |
title_fullStr | Biomedical informatics applications for precision management of neurodegenerative diseases |
title_full_unstemmed | Biomedical informatics applications for precision management of neurodegenerative diseases |
title_short | Biomedical informatics applications for precision management of neurodegenerative diseases |
title_sort | biomedical informatics applications for precision management of neurodegenerative diseases |
topic | Special Issue from the Centers of Biomedical Research Excellence (COBRE) and Center for Neurodegeneration and Translational Neuroscience (CNTN) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6118097/ https://www.ncbi.nlm.nih.gov/pubmed/30175230 http://dx.doi.org/10.1016/j.trci.2018.03.007 |
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