Dental Severity Assessment through Few-shot Learning and SBERT Fine-tuning

arXiv:2402.15755v1 Announce Type: new
Abstract: Dental diseases have a significant impact on a considerable portion of the population, leading to various health issues that can detrimentally affect individuals' overall well-being. The integration of automated systems in oral healthcare has become increasingly crucial. Machine learning approaches offer a viable solution to address challenges such as diagnostic difficulties, inefficiencies, and errors in oral disease diagnosis. These methods prove particularly useful when physicians struggle to predict or diagnose diseases at their early stages. …

abstract arxiv assessment automated become cs.cl dental diseases few-shot few-shot learning fine-tuning health healthcare impact integration machine machine learning population sbert solution systems through type