Mouth and oral disease classification using InceptionResNetV2 method - Rashid, Javed; Qaisar, Bilal Shabbir; Faheem, Muhammad; Akram, Arslan; Amin, Riaz ul; Hamid, Muhammad (Springer, 2024)
Digital tools have greatly improved the detection and diagnosis of oral and dental disorders like cancer and gum disease. Lip or oral cavity cancer is more likely to develop in those with potentially malignant oral disorders. A potentially malignant disorder (PMD) and debilitating condition of the oral mucosa, oral submucous fibrosis (OSMF), can have devastating effects on one’s quality of life. Incorporating deep learning into diagnosing conditions affecting the mouth and oral cavity is challenging. Mouth and Oral Diseases Classification using InceptionResNetV2 Method was established in the current study to identify diseases such as gangivostomatitis (Gum), canker sores (CaS), cold sores (CoS), oral lichen planus (OLP), oral thrush (OT), mouth cancer (MC), and oral cancer (OC). The new collection, termed "Mouth and Oral Diseases" (MOD), comprises seven distinct categories of data. Compared to state-of-the-art approaches, the proposed InceptionResNetV2 model’s 99.51% accuracy is significantly higher.
Keywords: InceptionResNetV2; Mouth and oral diseases dataset; Mouth diseases; Oral diseases; Teeth diseases; fi=Tietotekniikka|en=Computer Science|