Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution

arXiv:2402.14039v1 Announce Type: new
Abstract: The Covid-19 pandemic has led to an increase in the awareness of and demand for telemedicine services, resulting in a need for automating the process and relying on machine learning (ML) to reduce the operational load. This research proposes a specialty detection classifier based on a machine learning model to automate the process of detecting the correct specialty for each question and routing it to the correct doctor. The study focuses on handling multiclass and …

abstract arxiv class context covid covid-19 covid-19 pandemic cs.ai cs.lg demand detection distribution machine machine learning pandemic process reduce research services telemedicine type