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Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care
Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8634654/ https://www.ncbi.nlm.nih.gov/pubmed/34867524 http://dx.doi.org/10.3389/fpsyt.2021.734909 |
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author | Renn, Brenna N. Schurr, Matthew Zaslavsky, Oleg Pratap, Abhishek |
author_facet | Renn, Brenna N. Schurr, Matthew Zaslavsky, Oleg Pratap, Abhishek |
author_sort | Renn, Brenna N. |
collection | PubMed |
description | Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists and engineers and runs the risk of being disconnected from pragmatic issues in clinical practice. This interprofessional perspective bridges the experiences of clinical scientists and data science. We provide a brief overview of AI with the main focus on possible applications and challenges of using AI-based approaches for research and clinical care in geriatric mental health. We suggest future AI applications in geriatric mental health consider pragmatic considerations of clinical practice, methodological differences between data and clinical science, and address issues of ethics, privacy, and trust. |
format | Online Article Text |
id | pubmed-8634654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86346542021-12-02 Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care Renn, Brenna N. Schurr, Matthew Zaslavsky, Oleg Pratap, Abhishek Front Psychiatry Psychiatry Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists and engineers and runs the risk of being disconnected from pragmatic issues in clinical practice. This interprofessional perspective bridges the experiences of clinical scientists and data science. We provide a brief overview of AI with the main focus on possible applications and challenges of using AI-based approaches for research and clinical care in geriatric mental health. We suggest future AI applications in geriatric mental health consider pragmatic considerations of clinical practice, methodological differences between data and clinical science, and address issues of ethics, privacy, and trust. Frontiers Media S.A. 2021-11-15 /pmc/articles/PMC8634654/ /pubmed/34867524 http://dx.doi.org/10.3389/fpsyt.2021.734909 Text en Copyright © 2021 Renn, Schurr, Zaslavsky and Pratap. 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 | Psychiatry Renn, Brenna N. Schurr, Matthew Zaslavsky, Oleg Pratap, Abhishek Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title | Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title_full | Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title_fullStr | Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title_full_unstemmed | Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title_short | Artificial Intelligence: An Interprofessional Perspective on Implications for Geriatric Mental Health Research and Care |
title_sort | artificial intelligence: an interprofessional perspective on implications for geriatric mental health research and care |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8634654/ https://www.ncbi.nlm.nih.gov/pubmed/34867524 http://dx.doi.org/10.3389/fpsyt.2021.734909 |
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