Demystifying artificial intelligence and deep learning in dentistry
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Oral Research |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-83242021000100604 |
Resumo: | Abstract Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, capturing its intrinsic statistical patterns and structures. Neural networks (NNs) have been increasingly employed for ML complex data. The application of multilayered NN is referred to as “deep learning”, which has been recently investigated in dentistry. Convolutional neural networks (CNNs) are mainly used for processing large and complex imagery data, as they are able to extract image features like edges, corners, shapes, and macroscopic patterns using layers of filters. CNN algorithms allow to perform tasks like image classification, object detection and segmentation. The literature involving AI in dentistry has increased rapidly, so a methodological guidance for designing, conducting and reporting studies must be rigorously followed, including the improvement of datasets. The limited interaction between the dental field and the technical disciplines, however, remains a hurdle for applicable dental AI. Similarly, dental users must understand why and how AI applications work and decide to appraise their decisions critically. Generalizable and robust AI applications will eventually prove helpful for clinicians and patients alike. |
id |
SBPQO-1_75de0f0066984af1ed8dd3aae037bbc3 |
---|---|
oai_identifier_str |
oai:scielo:S1806-83242021000100604 |
network_acronym_str |
SBPQO-1 |
network_name_str |
Brazilian Oral Research |
repository_id_str |
|
spelling |
Demystifying artificial intelligence and deep learning in dentistryArtificial IntelligenceDeep LearningNeural Networks, ComputerDiagnostic ImagingDentistryAbstract Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, capturing its intrinsic statistical patterns and structures. Neural networks (NNs) have been increasingly employed for ML complex data. The application of multilayered NN is referred to as “deep learning”, which has been recently investigated in dentistry. Convolutional neural networks (CNNs) are mainly used for processing large and complex imagery data, as they are able to extract image features like edges, corners, shapes, and macroscopic patterns using layers of filters. CNN algorithms allow to perform tasks like image classification, object detection and segmentation. The literature involving AI in dentistry has increased rapidly, so a methodological guidance for designing, conducting and reporting studies must be rigorously followed, including the improvement of datasets. The limited interaction between the dental field and the technical disciplines, however, remains a hurdle for applicable dental AI. Similarly, dental users must understand why and how AI applications work and decide to appraise their decisions critically. Generalizable and robust AI applications will eventually prove helpful for clinicians and patients alike.Sociedade Brasileira de Pesquisa Odontológica - SBPqO2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-83242021000100604Brazilian Oral Research v.35 2021reponame:Brazilian Oral Researchinstname:Sociedade Brasileira de Pesquisa Odontológica (SBPqO)instacron:SBPQO10.1590/1807-3107bor-2021.vol35.0094info:eu-repo/semantics/openAccessRODRIGUES,Jonas AlmeidaKROIS,JoachimSCHWENDICKE,Falkeng2021-08-11T00:00:00Zoai:scielo:S1806-83242021000100604Revistahttps://www.scielo.br/j/bor/https://old.scielo.br/oai/scielo-oai.phppob@edu.usp.br||bor@sbpqo.org.br1807-31071806-8324opendoar:2021-08-11T00:00Brazilian Oral Research - Sociedade Brasileira de Pesquisa Odontológica (SBPqO)false |
dc.title.none.fl_str_mv |
Demystifying artificial intelligence and deep learning in dentistry |
title |
Demystifying artificial intelligence and deep learning in dentistry |
spellingShingle |
Demystifying artificial intelligence and deep learning in dentistry RODRIGUES,Jonas Almeida Artificial Intelligence Deep Learning Neural Networks, Computer Diagnostic Imaging Dentistry |
title_short |
Demystifying artificial intelligence and deep learning in dentistry |
title_full |
Demystifying artificial intelligence and deep learning in dentistry |
title_fullStr |
Demystifying artificial intelligence and deep learning in dentistry |
title_full_unstemmed |
Demystifying artificial intelligence and deep learning in dentistry |
title_sort |
Demystifying artificial intelligence and deep learning in dentistry |
author |
RODRIGUES,Jonas Almeida |
author_facet |
RODRIGUES,Jonas Almeida KROIS,Joachim SCHWENDICKE,Falk |
author_role |
author |
author2 |
KROIS,Joachim SCHWENDICKE,Falk |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
RODRIGUES,Jonas Almeida KROIS,Joachim SCHWENDICKE,Falk |
dc.subject.por.fl_str_mv |
Artificial Intelligence Deep Learning Neural Networks, Computer Diagnostic Imaging Dentistry |
topic |
Artificial Intelligence Deep Learning Neural Networks, Computer Diagnostic Imaging Dentistry |
description |
Abstract Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, capturing its intrinsic statistical patterns and structures. Neural networks (NNs) have been increasingly employed for ML complex data. The application of multilayered NN is referred to as “deep learning”, which has been recently investigated in dentistry. Convolutional neural networks (CNNs) are mainly used for processing large and complex imagery data, as they are able to extract image features like edges, corners, shapes, and macroscopic patterns using layers of filters. CNN algorithms allow to perform tasks like image classification, object detection and segmentation. The literature involving AI in dentistry has increased rapidly, so a methodological guidance for designing, conducting and reporting studies must be rigorously followed, including the improvement of datasets. The limited interaction between the dental field and the technical disciplines, however, remains a hurdle for applicable dental AI. Similarly, dental users must understand why and how AI applications work and decide to appraise their decisions critically. Generalizable and robust AI applications will eventually prove helpful for clinicians and patients alike. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-83242021000100604 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-83242021000100604 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-3107bor-2021.vol35.0094 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Odontológica - SBPqO |
publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Odontológica - SBPqO |
dc.source.none.fl_str_mv |
Brazilian Oral Research v.35 2021 reponame:Brazilian Oral Research instname:Sociedade Brasileira de Pesquisa Odontológica (SBPqO) instacron:SBPQO |
instname_str |
Sociedade Brasileira de Pesquisa Odontológica (SBPqO) |
instacron_str |
SBPQO |
institution |
SBPQO |
reponame_str |
Brazilian Oral Research |
collection |
Brazilian Oral Research |
repository.name.fl_str_mv |
Brazilian Oral Research - Sociedade Brasileira de Pesquisa Odontológica (SBPqO) |
repository.mail.fl_str_mv |
pob@edu.usp.br||bor@sbpqo.org.br |
_version_ |
1750318328056905728 |