Oral cancer (OC) presents a global burden on society and the healthcare system with high incidence rates and poor prognosis. Despite the oral cavity being easily accessible for visual assessment, lesions are often detected at an advanced stage when the prognosis is poor and radical interventions are necessary. An invasive biopsy of a clinically suspicious lesion is the current standard of care for OC diagnosis and lesion monitoring; however, repeated biopsies may not be feasible. This study aims to provide a non-invasive, objective, and accurate OC diagnostic test using high throughput DNA-based cytometry. This test combines artificial intelligence software with a commercially available and affordable slide scanner. Potentially, this new technique can be used in remote communities with limited access to care and provides a significant benefit in early detection of at-risk oral lesions and reduction in OC burdens.