Clinical decision support systems in orthodontics: A narrative review of data science approaches

Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high‐end computing soluti...

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Vydáno v:	Orthodontics & craniofacial research Ročník 24; číslo S2; s. 26 - 36
Hlavní autoři:	Al Turkestani, Najla, Bianchi, Jonas, Deleat‐Besson, Romain, Le, Celia, Tengfei, Li, Prieto, Juan Carlos, Gurgel, Marcela, Ruellas, Antonio C. O., Massaro, Camila, Aliaga Del Castillo, Aron, Evangelista, Karine, Yatabe, Marilia, Benavides, Erika, Soki, Fabiana, Zhang, Winston, Najarian, Kayvan, Gryak, Jonathan, Styner, Martin, Fillion‐Robin, Jean‐Christophe, Paniagua, Beatriz, Soroushmehr, Reza, Cevidanes, Lucia H. S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Wiley Subscription Services, Inc 01.12.2021
Témata:	Artificial Intelligence Data collection Data processing Data Science Data storage Decision support systems Decision Support Systems, Clinical Health care Learning algorithms Machine Learning Medical equipment Orthodontics Temporomandibular joint Well being orthodontics machine learning artificial intelligence decision support systems
ISSN:	1601-6335, 1601-6343, 1601-6343
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Abstract	Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high‐end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well‐being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In‐depth data analysis; and (d) Data communication. Then, we introduce a web‐based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.
AbstractList	Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems. Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.
Author	Le, Celia Yatabe, Marilia Fillion‐Robin, Jean‐Christophe Benavides, Erika Paniagua, Beatriz Tengfei, Li Gryak, Jonathan Evangelista, Karine Soroushmehr, Reza Deleat‐Besson, Romain Zhang, Winston Styner, Martin Al Turkestani, Najla Bianchi, Jonas Gurgel, Marcela Prieto, Juan Carlos Soki, Fabiana Najarian, Kayvan Ruellas, Antonio C. O. Aliaga Del Castillo, Aron Cevidanes, Lucia H. S. Massaro, Camila
AuthorAffiliation	10 Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA 9 Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, Ann Arbor, MI, USA 3 Department of Orthodontics, Arthur A. Dugoni School of Dentistry, University of the Pacific, San Francisco, CA, USA 11 Departments Psychiatry and Computer Science, University of North Carolina, Chapel Hill, NC, USA 12 Kitware Inc., Carrboro, NC, USA 8 Department of Orthodontics, School of Dentistry, University of Goias, Goiania, Brazil 2 Department of Restorative and Aesthetic Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia 6 Department of Orthodontics, School of Dentistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil 1 Department of Orthodontics and Pediatric Dentistry, University of Michigan School of Dentistry, Ann Arbor, MI, USA 4 Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA 7 Department of Orthod
AuthorAffiliation_xml	– name: 2 Department of Restorative and Aesthetic Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia – name: 3 Department of Orthodontics, Arthur A. Dugoni School of Dentistry, University of the Pacific, San Francisco, CA, USA – name: 7 Department of Orthodontics, Bauru Dental School, University of São Paulo, São Paulo, Brazil – name: 1 Department of Orthodontics and Pediatric Dentistry, University of Michigan School of Dentistry, Ann Arbor, MI, USA – name: 6 Department of Orthodontics, School of Dentistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil – name: 10 Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA – name: 12 Kitware Inc., Carrboro, NC, USA – name: 8 Department of Orthodontics, School of Dentistry, University of Goias, Goiania, Brazil – name: 9 Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, Ann Arbor, MI, USA – name: 5 Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA – name: 4 Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA – name: 11 Departments Psychiatry and Computer Science, University of North Carolina, Chapel Hill, NC, USA
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BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33973362$$D View this record in MEDLINE/PubMed
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Copyright	2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. Copyright © 2021 John Wiley & Sons A/S
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 AUTHOR CONTRIBUTIONS Najla N. Al Turkestani: Formal analysis, Investigation, Methodology, Writing original draft. Jonas Bianchi, Marcela Gurgel, Camila Massaro, Aron Aliaga Del Castillo, Karine Evangelista, Marilia Yatabe: Writing–review & editing. Romain Deleat-Besson, Celia Le, Juan Carlos Prieto, Winston Zhang, Kayvan Najarian, Jonathan Gryak, Martin Styner, Jean-Christophe Fillion-Robin, Beatriz Paniagua, Reza Soroushmehr: software engineering, Writing–review & editing. Li Tengfei: statistician, Writing – review & editing. Antonio Ruellas: Methodology, Writing–review & editing. Erika Benavides, Fabiana; radiological image interpretation, Writing–review & editing. Lucia Cevidanes: Conceptualization, Formal analysis, Investigation, Methodology, Writing–review & editing.
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SubjectTerms	Artificial Intelligence Data collection Data processing Data Science Data storage Decision support systems Decision Support Systems, Clinical Health care Learning algorithms Machine Learning Medical equipment Orthodontics Temporomandibular joint Well being
Title	Clinical decision support systems in orthodontics: A narrative review of data science approaches
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