Decoding Deep Learning applications for diagnosis and treatment planning

Decoding Deep Learning applications for diagnosis and treatment planning

ABSTRACT Introduction: Artificial Intelligence (AI), Machine Learning and Deep Learning are playing an increasingly significant role in the medical field in the 21st century. These recent technologies are based on the concept of creating machines that have the potential to function as a human brain. It necessitates the gathering of large quantity of data to be processed. Once processed with AI machines, these data have the potential to streamline and improve the capabilities of the medical field in diagnosis and treatment planning, as well as in the prediction and recognition of diseases. These concepts are new to Orthodontics and are currently limited to image processing and pattern recognition. Objective: This article exposes and describes the different methods by which orthodontics may benefit from a more widespread adoption of these technologies.

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Main Authors: RETROUVEY,Jean-Marc, CONLEY,Richard Scott
Format: Digital revista
Language:English
Published: Dental Press International 2022
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2176-94512022000500500
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spelling oai:scielo:S2176-945120220005005002022-12-21Decoding Deep Learning applications for diagnosis and treatment planningRETROUVEY,Jean-MarcCONLEY,Richard Scott Deep learning Artificial intelligence Orthodontics ABSTRACT Introduction: Artificial Intelligence (AI), Machine Learning and Deep Learning are playing an increasingly significant role in the medical field in the 21st century. These recent technologies are based on the concept of creating machines that have the potential to function as a human brain. It necessitates the gathering of large quantity of data to be processed. Once processed with AI machines, these data have the potential to streamline and improve the capabilities of the medical field in diagnosis and treatment planning, as well as in the prediction and recognition of diseases. These concepts are new to Orthodontics and are currently limited to image processing and pattern recognition. Objective: This article exposes and describes the different methods by which orthodontics may benefit from a more widespread adoption of these technologies.info:eu-repo/semantics/openAccessDental Press InternationalDental Press Journal of Orthodontics v.27 n.5 20222022-01-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2176-94512022000500500en10.1590/2177-6709.27.5.e22spe5
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country Brasil
countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author RETROUVEY,Jean-Marc
CONLEY,Richard Scott
spellingShingle RETROUVEY,Jean-Marc
CONLEY,Richard Scott
Decoding Deep Learning applications for diagnosis and treatment planning
author_facet RETROUVEY,Jean-Marc
CONLEY,Richard Scott
author_sort RETROUVEY,Jean-Marc
title Decoding Deep Learning applications for diagnosis and treatment planning
title_short Decoding Deep Learning applications for diagnosis and treatment planning
title_full Decoding Deep Learning applications for diagnosis and treatment planning
title_fullStr Decoding Deep Learning applications for diagnosis and treatment planning
title_full_unstemmed Decoding Deep Learning applications for diagnosis and treatment planning
title_sort decoding deep learning applications for diagnosis and treatment planning
description ABSTRACT Introduction: Artificial Intelligence (AI), Machine Learning and Deep Learning are playing an increasingly significant role in the medical field in the 21st century. These recent technologies are based on the concept of creating machines that have the potential to function as a human brain. It necessitates the gathering of large quantity of data to be processed. Once processed with AI machines, these data have the potential to streamline and improve the capabilities of the medical field in diagnosis and treatment planning, as well as in the prediction and recognition of diseases. These concepts are new to Orthodontics and are currently limited to image processing and pattern recognition. Objective: This article exposes and describes the different methods by which orthodontics may benefit from a more widespread adoption of these technologies.
publisher Dental Press International
publishDate 2022
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2176-94512022000500500
work_keys_str_mv AT retrouveyjeanmarc decodingdeeplearningapplicationsfordiagnosisandtreatmentplanning
AT conleyrichardscott decodingdeeplearningapplicationsfordiagnosisandtreatmentplanning
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