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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Selcuk University Press
2020-08-01
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| Series: | Selcuk Dental Journal |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/download/article-file/1201319 |
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| Summary: | 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. |
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| ISSN: | 2148-7529 |