Weiter zum Inhalt

Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants

Implants are now the standard method of replacing missing or damaged teeth. Despite the improving technologies for the manufacture of implants and the introduction of new protocols for diagnosing, planning, and performing implant placement operations, the percentage of complications in the early pos...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Lyakhov, P. A., Ляхов, П. А., Lyakhova, U. A., Ляхова, У. А.
Format: Статья
Sprache:English
Veröffentlicht: 2023
Schlagworte:
Online Zugang:https://dspace.ncfu.ru/handle/20.500.12258/22297
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
id ir-20.500.12258-22297
record_format dspace
spelling ir-20.500.12258-222972023-02-03T07:30:00Z Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants Lyakhov, P. A. Ляхов, П. А. Lyakhova, U. A. Ляхова, У. А. Big data Health information technology Digital data processing Dentistry Dental implantation Survival Data mining Artificial neural network Implants are now the standard method of replacing missing or damaged teeth. Despite the improving technologies for the manufacture of implants and the introduction of new protocols for diagnosing, planning, and performing implant placement operations, the percentage of complications in the early postoperative period remains quite high. In this regard, there is a need to develop new methods for preliminary assessment of the patient’s condition to predict the success of single implant survival. The intensive development of artificial intelligence technologies and the increase in the amount of digital information that is available for analysis make it relevant to develop systems based on neural networks for auxiliary diagnostics and forecasting. Systems based on artificial intelligence in the field of dental implantology can become one of the methods for forming a second opinion based on mathematical decision making and forecasting. The actual clinical evaluation of a particular case and further treatment are carried out by the dentist, and AI-based systems can become an integral part of additional diagnostics. The article proposes an artificial intelligence system for analyzing various patient statistics to predict the success of single implant survival. As the topology of the neural network, the most optimal linear neural network architectures were developed. The one-hot encoding method was used as a preprocessing method for statistical data. The novelty of the proposed system lies in the developed optimal neural network architecture designed to recognize the collected and digitized database of various patient factors based on the description of the case histories. The accuracy of recognition of statistical factors of patients for predicting the success of single implants in the proposed system was 94.48%. The proposed neural network system makes it possible to achieve higher recognition accuracy than similar neural network prediction systems due to the analysis of a large number of statistical factors of patients. The use of the proposed system based on artificial intelligence will allow the implantologist to pay attention to the insignificant factors affecting the quality of the installation and the further survival of the implant, and reduce the percentage of complications at all stages of treatment. However, the developed system is not a medical device and cannot independently diagnose patients. At this point, the neural network system for analyzing the statistical factors of patients can predict a positive or negative outcome of a single dental implant operation and cannot be used as a full-fledged tool for supporting medical decision-making. 2023-02-03T07:29:10Z 2023-02-03T07:29:10Z 2022 Статья Lyakhov, P.A., Dolgalev, A.A., Lyakhova, U.A., Muraev, A.A., Zolotayev, K.E., Semerikov, D.Y. Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants // Frontiers in Neuroinformatics. - 2022. - 16, статья № 1067040. - DOI: 10.3389/fninf.2022.1067040 http://hdl.handle.net/20.500.12258/22297 en Frontiers in Neuroinformatics application/pdf application/pdf
institution СКФУ
collection Репозиторий
language English
topic Big data
Health information technology
Digital data processing
Dentistry
Dental implantation
Survival
Data mining
Artificial neural network
spellingShingle Big data
Health information technology
Digital data processing
Dentistry
Dental implantation
Survival
Data mining
Artificial neural network
Lyakhov, P. A.
Ляхов, П. А.
Lyakhova, U. A.
Ляхова, У. А.
Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
description Implants are now the standard method of replacing missing or damaged teeth. Despite the improving technologies for the manufacture of implants and the introduction of new protocols for diagnosing, planning, and performing implant placement operations, the percentage of complications in the early postoperative period remains quite high. In this regard, there is a need to develop new methods for preliminary assessment of the patient’s condition to predict the success of single implant survival. The intensive development of artificial intelligence technologies and the increase in the amount of digital information that is available for analysis make it relevant to develop systems based on neural networks for auxiliary diagnostics and forecasting. Systems based on artificial intelligence in the field of dental implantology can become one of the methods for forming a second opinion based on mathematical decision making and forecasting. The actual clinical evaluation of a particular case and further treatment are carried out by the dentist, and AI-based systems can become an integral part of additional diagnostics. The article proposes an artificial intelligence system for analyzing various patient statistics to predict the success of single implant survival. As the topology of the neural network, the most optimal linear neural network architectures were developed. The one-hot encoding method was used as a preprocessing method for statistical data. The novelty of the proposed system lies in the developed optimal neural network architecture designed to recognize the collected and digitized database of various patient factors based on the description of the case histories. The accuracy of recognition of statistical factors of patients for predicting the success of single implants in the proposed system was 94.48%. The proposed neural network system makes it possible to achieve higher recognition accuracy than similar neural network prediction systems due to the analysis of a large number of statistical factors of patients. The use of the proposed system based on artificial intelligence will allow the implantologist to pay attention to the insignificant factors affecting the quality of the installation and the further survival of the implant, and reduce the percentage of complications at all stages of treatment. However, the developed system is not a medical device and cannot independently diagnose patients. At this point, the neural network system for analyzing the statistical factors of patients can predict a positive or negative outcome of a single dental implant operation and cannot be used as a full-fledged tool for supporting medical decision-making.
format Статья
author Lyakhov, P. A.
Ляхов, П. А.
Lyakhova, U. A.
Ляхова, У. А.
author_facet Lyakhov, P. A.
Ляхов, П. А.
Lyakhova, U. A.
Ляхова, У. А.
author_sort Lyakhov, P. A.
title Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
title_short Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
title_full Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
title_fullStr Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
title_full_unstemmed Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
title_sort neural network system for analyzing statistical factors of patients for predicting the survival of dental implants
publishDate 2023
url https://dspace.ncfu.ru/handle/20.500.12258/22297
work_keys_str_mv AT lyakhovpa neuralnetworksystemforanalyzingstatisticalfactorsofpatientsforpredictingthesurvivalofdentalimplants
AT lâhovpa neuralnetworksystemforanalyzingstatisticalfactorsofpatientsforpredictingthesurvivalofdentalimplants
AT lyakhovaua neuralnetworksystemforanalyzingstatisticalfactorsofpatientsforpredictingthesurvivalofdentalimplants
AT lâhovaua neuralnetworksystemforanalyzingstatisticalfactorsofpatientsforpredictingthesurvivalofdentalimplants
_version_ 1760599781116215296