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NAMDAR PEKİNER, FİLİZ MEDİHA

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NAMDAR PEKİNER

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FİLİZ MEDİHA

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Author: KESER, GAYE × Subject: Dental Hygiene ×

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    PublicationOpen Access
    Plaut-vincent stomatitis: A case report
    (2023-12-01) ÜNAL, SUAY YAĞMUR; KESER, GAYE; NAMDAR PEKİNER, FİLİZ MEDİHA; Ünal S. Y., Keser G., Namdar Pekiner F. M.
    Necrotizing ulcerative stomatitis or Plaut-Vincent’s Stomatitis is a complication of necrotizing ulcerative gingivitis that extends beyond the gingiva and is involved in other parts of the oral mucosa, with Fusiform bacillus, Borrelia vincenti and other anaerobic microorganisms being the most common associated bacteria. It starts with sore throat, bad smell in the mouth, bleeding gums in young adults with poor oral hygiene and decreased immune resistance. In this case, clinical findings of Plaut-Vincent Stomatitis belonging to a male patient are presented. In a 22-yearold male patient, erythematous, ulcers with irregular margins and grayish-white fibrin were observed in the soft tissue of the right third molar region of the mandible and in the buccal mucosa. The patient has halitosis, difficulty in swallowing, pain in the oropharynx, and lymphadenopathy. In the treatment of infected tissues, improvement was observed after systemic antibiotics and hydrogen peroxide mouthwash were applied for 6-7 days. PlautVincent Stomatitis is frequently seen in young adults and poor oral hygiene, smoking, emotional stress, alcohol consumption and malnutrition are stated as etiological factors that predispose to this disease. Detection of ulcerated lesions in soft tissue examination is important in diagnosis and treatment.
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    PublicationOpen Access
    A deep learning algorithm for classification of oral lichen planus lesions from photographic images: a retrospective study
    (2023-02-01) NAMDAR PEKİNER, FİLİZ MEDİHA; KESER, GAYE; Keser G., Bayrakdar İ. Ş., Namdar Pekiner F. M., Çelik Ö., Orhan K.
    IntroductionDeep learning methods have recently been applied for the processing of medical images, and they have shown promise in a variety of applications. This study aimed to develop a deep learning approach for identifying oral lichen planus lesions using photographic images.Material and MethodsAnonymous retrospective photographic images of buccal mucosa with 65 healthy and 72 oral lichen planus lesions were identified using the CranioCatch program (CranioCatch, Eskişehir, Turkey). All images were re-checked and verified by Oral Medicine and Maxillofacial Radiology experts. This data set was divided into training (n =51; n=58), verification (n =7; n=7), and test (n =7; n=7) sets for healthy mucosa and mucosa with the oral lichen planus lesion, respectively. In the study, an artificial intelligence model was developed using Google Inception V3 architecture implemented with Tensorflow, which is a deep learning approach.ResultsAI deep learning model provided the classification of all test images for both healthy and diseased mucosa with a 100% success rate.ConclusionIn the healthcare business, AI offers a wide range of uses and applications. The increased effort increased complexity of the job, and probable doctor fatigue may jeopardize diagnostic abilities and results. Artificial intelligence (AI) components in imaging equipment would lessen this effort and increase efficiency. They can also detect oral lesions and have access to more data than their human counterparts. Our preliminary findings show that deep learning has the potential to handle this significant challenge.