The innovation of AI-based software in oral diseases: clinical-histopathological correlation diagnostic accuracy primary study.

BACKGROUND: Machine learning (ML) through artificial intelligence (AI) could provide clinicians and oral pathologists to advance diagnostic problems in the field of potentially malignant lesions, oral cancer, periodontal diseases, salivary gland disease, oral infections, immune-mediated disease, and others. AI can detect micro-features beyond human eyes and provide solution in critical diagnostic cases. OBJECTIVE: The objective of this study was developing a software with all needed feeding data to act as AI-based program to diagnose oral diseases. So our research question was: Can we develop a Computer-Aided Software for accurate diagnosis of oral diseases based on clinical and histopathological data inputs? METHOD: The study sample included clinical images, patient symptoms, radiographic images, histopathological images and texts for the oral diseases of interest in the current study (premalignant lesions, oral cancer, salivary gland neoplasms, immune mediated oral mucosal lesions, oral reactive lesions) total oral diseases enrolled in this study was 28 diseases retrieved from the archives of oral maxillofacial pathology department. Total 11,200 texts and 3000 images (2800 images were used for training data to the program and 100 images were used as test data to the program and 100 cases for calculating accuracy, sensitivity& specificity). RESULTS: The correct diagnosis rates for group 1 (software users), group 2 (microscopic users) and group 3 (hybrid) were 87%, 90.6, 95% respectively. The reliability for inter-observer value was done by calculating Cronbach's alpha and interclass correlation coefficient. The test revealed for group 1, 2 and 3 the following values respectively 0.934, 0.712 & 0.703. All groups showed acceptable reliability especially for Diagnosis Oral Diseases Software (DODS) that revealed higher reliability value than other groups. However, The accuracy, sensitivity & specificity of this software was lower than those of oral pathologists (master's degree). CONCLUSION: The correct diagnosis rate of DODS was comparable to oral pathologists using standard microscopic examination. The DODS program could be utilized as diagnostic guidance tool with high reliability & accuracy.

The anti-fungal effect of miconazole and miconazole-loaded chitosan nanoparticles gels in diabetic patients with Oral candidiasis-randomized control clinical trial and microbiological analysis.

BACKGROUND: Oral thrush is the most common occurring fungal infection in the oral cavity in uncontrolled diabetic patients, it is treated by various antifungal drugs according to each case. This study aimed to evaluate the therapeutic effects of topical application of miconazole and miconazole-loaded chitosan nanoparticles in treatment of diabetic patients with oral candidiasis. METHODS: In this randomized controlled clinical trial. A total of 80 diabetic patients presenting with symptomatic oral candidiasis were randomly assigned into two treatment groups: miconazole and miconazole-loaded chitosan nanoparticles. The patients were treated for 28 days, and clinical assessments were conducted at baseline, 7, 14, 21 and 28 days. Clinical parameters, including signs and symptoms of oral candidiasis were evaluated and microbiological analysis was performed to determine the Candida species and assess their susceptibility to the antifungal agents. Statistical analysis was done to the categorical and numerical data using chi-square test and Kruskal Wallis test. RESULTS: The antifungal efficacy between the miconazole and miconazole-loaded chitosan nanoparticles (CS-MCZ) groups insignificant difference (P >  0.05) was observed. Both treatment modalities exhibited comparable effectiveness in controlling oral candidiasis symptoms and reducing Candida colonization as miconazole-loaded chitosan nanoparticles group showed a significant difference in the clinical improvement in respect of both signs and symptoms from baseline (70%) until the end of study at 28 days (5%) (P <  0.05) Moreover, miconazole-loaded chitosan nanoparticles, there was a significant reduction in the number of colonies forming units of Candida albicans from baseline until the end of the study at 28-day with P value <  0.000. CONCLUSIONS: This randomized controlled clinical trial and microbiological analysis demonstrate that both miconazole and miconazole-loaded chitosan nanoparticles are effective in the treatment of oral candidiasis in diabetic patients with no adverse reactions. TRIAL REGISTRATION: NCT06072716 with first registration first registration in 10/10/2023.