Use of Artificial Intelligence in automated analysis of liquid-based oral brush cytology – Development of a screening tool for head and neck cancers based on Deep Learning algorithms

Background Oral squamous cell carcinomas (OSCCs) clinically present with a heterogenous appearance. To improve the prognosis of patients with OSCC, it is imperative to ensure early and accurate diagnosis. Exfoliative cytology is a simple, cost-effective and non-invasive diagnostic tool for early detection of oral malignant lesions. This study evaluated the efficacy of artificial intelligence with Deep Learning in analysing smears of suspicious oral lesions, as compared to conventional cytopathologic assessment and histopathology. The reliability of the AI was evaluated in terms of sensitivity and specificity.