A deep learning algorithm for classification of oral lichen planus lesions from photographic images: a retrospective study - NAMDAR PEKİNER, FİLİZ MEDİHA; KESER, GAYE (My University, 2023)
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.
Keywords: Diş Hekimliği; Klinik Bilimler; Oral Diagnoz ve Radyoloji; Bilgisayar Bilimleri; Yapay Zeka, Bilgisayarda Öğrenme ve Örüntü Tanıma; Sağlık Bilimleri; Mühendislik ve Teknoloji; Dentistry; Clinical Sciences; Oral Diagnosis and Radiology; Computer Sciences; Artificial Intelligence, Computer Learning and Pattern Recognition; Health Sciences; Engineering and Technology; Klinik Tıp (MED); Mühendislik, Bilişim ve Teknoloji (ENG); Klinik Tıp; Bilgisayar Bilimi; DİŞ HEKİMLİĞİ, ORAL CERRAHİ VE TIP; BİLGİSAYAR BİLİMİ, YAPAY ZEKA; Clinical Medicine (MED); Engineering, Computing & Technology (ENG); CLINICAL MEDICINE; COMPUTER SCIENCE; DENTISTRY, ORAL SURGERY & MEDICINE; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; Periodontoloji; Ortodonti; Ağız Cerrahisi; Diş Hijyeni; Dişçilik Hizmetleri; Diş Hekimliği (çeşitli); Bilgisayarla Görme ve Örüntü Tanıma; Bilgisayar Bilimi Uygulamaları; Yapay Zeka; Bilgisayar Bilimi (çeşitli); Genel Bilgisayar Bilimi; Fizik Bilimleri; Periodontics; Orthodontics; Oral Surgery; Dental Hygiene; Dental Assisting; Dentistry (miscellaneous); General Dentistry; Computer Vision and Pattern Recognition; Computer Science Applications; Artificial Intelligence; Computer Science (miscellaneous); General Computer Science; Physical Sciences; Oral lichen planus; Deep learning; Artificial intelligence; ARTIFICIAL-INTELLIGENCE; NEURAL-NETWORKS; APOPTOSIS; EXPRESSION