Diş Hekimliği Fakültesi / Faculty of Dentistry

Permanent URI for this collectionhttps://hdl.handle.net/11727/2120

Browse

Filters

2020 - 20233

Settings

Has files: Yessearch.filters.applied.f.rights: search.filters.rights.info:eu-repo/semantics/closedAccess

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Machine Learning Based Orthodontic Treatment Planning for Mixed Dentition Borderline Cases Suffering from Moderate to Severe Crowding: An Experimental Research Study
    (2023) Senirkentli, G. Burcu; Bingol, Sinem Ince; Unal, Metehan; Bostanci, Erkan; Guzel, Mehmet Serdar; Acici, Koray; 36970921
    BACKGROUND: Pedodontists and general practitioners may need support in planning the early orthodontic treatment of patients with mixed dentition, especially in borderline cases. The use of machine learning algorithms is required to be able to consistently make treatment decisions for such cases. OBJECTIVE: This study aimed to use machine learning algorithms to facilitate the process of deciding whether to choose serial extraction or expansion of maxillary and mandibular dental arches for early treatment of borderline patients suffering from moderate to severe crowding. METHODS: The dataset of 116 patients who were previously treated by senior orthodontists and divided into two groups according to their treatment modalities were examined. Machine Learning algorithms including Multilayer Perceptron, Linear Logistic Regression, k-nearest Neighbors, Naive Bayes, and Random Forest were trained on this dataset. Several metrics were used for the evaluation of accuracy, precision, recall, and kappa statistic. RESULTS: The most important 12 features were determined with the feature selection algorithm. While all algorithms achieved over 90% accuracy, Random Forest yielded 95% accuracy, with high reliability values (kappa = 0.90). CONCLUSION: The employment of machine learning methods for the treatment decision with or without extraction in the early treatment of patients in the mixed dentition can be particularly useful for pedodontists and general practitioners.
  • No Thumbnail Available
    Item
    Early Maxillary Expansion with the Ni-Ti Memory Leaf Expander-A Compliance-Free Fixed Slow Maxillary Expansion Screw: A Report of 2 Cases
    (2021) Ulug, Bahar; Ozcirpici, Ayca Arman; 35110164
    Transversal problems such as crowding and crossbite are one of the most common problems dealt with in early orthodontic treatments. Early correction of these problems may ease or even eliminate the future need for treatment. This paper presents the management of 2 cases with transverse discrepancy using the Ni-Ti Memory Leaf Expander-a new compliance-free slow maxillary expansion appliance. The total treatment time for both cases was 9 months. In both cases, the inter-canine, inter-premolar, and inter-molar distances, as well as the arch length, have all increased.
  • No Thumbnail Available
    Item
    A rare presentation of stafne bone cyst
    (2020) Bayrak, N. B.; 30769109
    Stafne bone cysts (SBC) are defined as pseudocysts of the jaw in the literature. These lesions are typically localized at lingual cortical surface of the mandible and generally included normal salivary gland tissue; but they do not contain an epithelial lining. They may contain fat, muscle, connective tissue, lymphatic tissue, nerve bundles, blood vessels or air. In the literature, unlike posterior variant of SBC, anterior type of SBC (aSBC) is almost seven times less common (0.009%-0.3%). Usually, SCBs are identified at dental examination randomly. Since these lesions are mostly asymptomatic, some additional imagining modalities such as magnetic resonance imaging (MRI), computed tomography (CT) or sialography may be useful to confirm the diagnosis for atypical lesions. The aim of this report is to present a new case of aSBC and focuses on differential diagnosis along with alternative diagnostic imaging resources and review current literature. (C) 2019 Elsevier Masson SAS. All rights reserved.