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A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias

Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer's disease and related dementias (ADRD). Systematic harmonization of data elements is neces...

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Autores principales: Shaaban, C. Elizabeth, Tudorascu, Dana L., Glymour, M. Maria, Cohen, Ann D., Thurston, Rebecca C., Snyder, Heather M., Hohman, Timothy J., Mukherjee, Shubhabrata, Yu, Lan, Snitz, Beth E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353763/
https://www.ncbi.nlm.nih.gov/pubmed/37464990
http://dx.doi.org/10.3389/fnimg.2022.978350
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author Shaaban, C. Elizabeth
Tudorascu, Dana L.
Glymour, M. Maria
Cohen, Ann D.
Thurston, Rebecca C.
Snyder, Heather M.
Hohman, Timothy J.
Mukherjee, Shubhabrata
Yu, Lan
Snitz, Beth E.
author_facet Shaaban, C. Elizabeth
Tudorascu, Dana L.
Glymour, M. Maria
Cohen, Ann D.
Thurston, Rebecca C.
Snyder, Heather M.
Hohman, Timothy J.
Mukherjee, Shubhabrata
Yu, Lan
Snitz, Beth E.
author_sort Shaaban, C. Elizabeth
collection PubMed
description Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer's disease and related dementias (ADRD). Systematic harmonization of data elements is necessary to pool information from heterogeneous samples, and such pooling allows more expansive evaluations of health disparities, more precise effect estimates, and more opportunities to discover effective prevention or treatment strategies. The key goal of this Tutorial in Population Neuroimaging Curriculum, Instruction, and Pedagogy article is to guide researchers in creating a customized population neuroscience of ADRD harmonization training plan to fit their needs or those of their mentees. We provide brief guidance for retrospective data harmonization of multiple data types in this area, including: (1) clinical and demographic, (2) neuropsychological, and (3) neuroimaging data. Core competencies and skills are reviewed, and resources are provided to fill gaps in training as well as data needs. We close with an example study in which harmonization is a critical tool. While several aspects of this tutorial focus specifically on ADRD, the concepts and resources are likely to benefit population neuroscientists working in a range of research areas.
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spelling pubmed-103537632023-07-18 A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias Shaaban, C. Elizabeth Tudorascu, Dana L. Glymour, M. Maria Cohen, Ann D. Thurston, Rebecca C. Snyder, Heather M. Hohman, Timothy J. Mukherjee, Shubhabrata Yu, Lan Snitz, Beth E. Front Neuroimaging Neuroimaging Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer's disease and related dementias (ADRD). Systematic harmonization of data elements is necessary to pool information from heterogeneous samples, and such pooling allows more expansive evaluations of health disparities, more precise effect estimates, and more opportunities to discover effective prevention or treatment strategies. The key goal of this Tutorial in Population Neuroimaging Curriculum, Instruction, and Pedagogy article is to guide researchers in creating a customized population neuroscience of ADRD harmonization training plan to fit their needs or those of their mentees. We provide brief guidance for retrospective data harmonization of multiple data types in this area, including: (1) clinical and demographic, (2) neuropsychological, and (3) neuroimaging data. Core competencies and skills are reviewed, and resources are provided to fill gaps in training as well as data needs. We close with an example study in which harmonization is a critical tool. While several aspects of this tutorial focus specifically on ADRD, the concepts and resources are likely to benefit population neuroscientists working in a range of research areas. Frontiers Media S.A. 2022-09-26 /pmc/articles/PMC10353763/ /pubmed/37464990 http://dx.doi.org/10.3389/fnimg.2022.978350 Text en Copyright © 2022 Shaaban, Tudorascu, Glymour, Cohen, Thurston, Snyder, Hohman, Mukherjee, Yu and Snitz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroimaging
Shaaban, C. Elizabeth
Tudorascu, Dana L.
Glymour, M. Maria
Cohen, Ann D.
Thurston, Rebecca C.
Snyder, Heather M.
Hohman, Timothy J.
Mukherjee, Shubhabrata
Yu, Lan
Snitz, Beth E.
A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title_full A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title_fullStr A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title_full_unstemmed A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title_short A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias
title_sort guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of alzheimer's disease and related dementias
topic Neuroimaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353763/
https://www.ncbi.nlm.nih.gov/pubmed/37464990
http://dx.doi.org/10.3389/fnimg.2022.978350
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