Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery
Background: Artificial Neural Network (ANN) is relatively crude electronic model based on the neural structure of human brain which was used in the field of medicine in different purposes. It can be used for many medical branches especially for estimating the course of a certain disorder or treatmen...
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| Format: | Article |
| Language: | English |
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Selcuk University Press
2020-08-01
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| Series: | Selcuk Dental Journal |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/1201319 |
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| author | Seda Kocyigit Okan Özgönenel Bora Ozden Burcu Baş Hatice Hosgor Ozlem Akbelen Kaya |
| author_facet | Seda Kocyigit Okan Özgönenel Bora Ozden Burcu Baş Hatice Hosgor Ozlem Akbelen Kaya |
| author_sort | Seda Kocyigit |
| collection | DOAJ |
| description | Background: Artificial Neural Network (ANN) is relatively crude electronic model
based on the neural structure of human brain which was used in the field of
medicine in different purposes. It can be used for
many medical branches especially for estimating
the course of a certain disorder or treatment procedure. The aim of this
study is to use ANN in maxillofacial surgery to estimate the postoperative
symptoms after third molar surgery.Methods:The pre and post-operative information of 175 consecutive patients who needed extraction of impacted third
molar teeth were employed to train an ANN. After the training
process, the information of 26 cases was
used in order to verify the network's ability to predict the post-operative
symptoms such as swelling, pain, decrease
of mouth opening, bleeding, number of days
to return to normal activities and duration of activity restriction. The results obtained from ANN were compared with
the results of patients self-reported information. The correlation between the postoperative symptoms of the patients and
outcomes obtained from the ANN were analyzed statistically.Results: Close association was
found between the patients’ reports and ANN
results on post-operative pain, swelling, bleeding, number of days to return to normal
activities and duration of activity restriction.Conclusions: The proposed ANN approach is easy to
implement and adapted to predict the
response of the postoperative outcomes.
The model can be further extended to include more variables and experimental
data to increase reliability.Keywords:Activity restriction, artificial
neural network, postoperative discomfort, third molar surgery. |
| format | Article |
| id | doaj-art-e60170f7f536450294620155d0c4c6cc |
| institution | Kabale University |
| issn | 2148-7529 |
| language | English |
| publishDate | 2020-08-01 |
| publisher | Selcuk University Press |
| record_format | Article |
| series | Selcuk Dental Journal |
| spelling | doaj-art-e60170f7f536450294620155d0c4c6cc2025-01-03T01:32:56ZengSelcuk University PressSelcuk Dental Journal2148-75292020-08-017214815410.15311/selcukdentj.535365154Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar SurgerySeda Kocyigit0Okan Özgönenel1Bora Ozden2Burcu Baş3Hatice Hosgor4Ozlem Akbelen Kaya5Istanbul Kucukcekmece Oral and Dental Health Hospital, Department of Oral and Maxillofacial SurgeryOndokuz Mayıs University, Faculty of Engineering,Department of Electrical and Electronic EngineeringOndokuz Mayıs University, Faculty of Dentistry,Department of Oral and Maxillofacial SurgeryOndokuz Mayıs University, Faculty of Dentistry,Department of Oral and Maxillofacial SurgeryKocaeli University, Faculty of Dentistry, Department of Oral and Maxillofacial SurgeryPrivate Dental Clinic, İzmirBackground: Artificial Neural Network (ANN) is relatively crude electronic model based on the neural structure of human brain which was used in the field of medicine in different purposes. It can be used for many medical branches especially for estimating the course of a certain disorder or treatment procedure. The aim of this study is to use ANN in maxillofacial surgery to estimate the postoperative symptoms after third molar surgery.Methods:The pre and post-operative information of 175 consecutive patients who needed extraction of impacted third molar teeth were employed to train an ANN. After the training process, the information of 26 cases was used in order to verify the network's ability to predict the post-operative symptoms such as swelling, pain, decrease of mouth opening, bleeding, number of days to return to normal activities and duration of activity restriction. The results obtained from ANN were compared with the results of patients self-reported information. The correlation between the postoperative symptoms of the patients and outcomes obtained from the ANN were analyzed statistically.Results: Close association was found between the patients’ reports and ANN results on post-operative pain, swelling, bleeding, number of days to return to normal activities and duration of activity restriction.Conclusions: The proposed ANN approach is easy to implement and adapted to predict the response of the postoperative outcomes. The model can be further extended to include more variables and experimental data to increase reliability.Keywords:Activity restriction, artificial neural network, postoperative discomfort, third molar surgery.https://dergipark.org.tr/tr/download/article-file/1201319activity restrictionartificial neural networkpostoperative discomfortthird molar surgeryaktivite kısıtlamasıüçüncü molar cerrahisipostoperatif rahatsızlıkyapay sinir ağı |
| spellingShingle | Seda Kocyigit Okan Özgönenel Bora Ozden Burcu Baş Hatice Hosgor Ozlem Akbelen Kaya Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery Selcuk Dental Journal activity restriction artificial neural network postoperative discomfort third molar surgery aktivite kısıtlaması üçüncü molar cerrahisi postoperatif rahatsızlık yapay sinir ağı |
| title | Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery |
| title_full | Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery |
| title_fullStr | Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery |
| title_full_unstemmed | Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery |
| title_short | Development of an Artificial Intelligence System to Estimate Postoperative Discomfort After Impacted Third Molar Surgery |
| title_sort | development of an artificial intelligence system to estimate postoperative discomfort after impacted third molar surgery |
| topic | activity restriction artificial neural network postoperative discomfort third molar surgery aktivite kısıtlaması üçüncü molar cerrahisi postoperatif rahatsızlık yapay sinir ağı |
| url | https://dergipark.org.tr/tr/download/article-file/1201319 |
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