In this paper, we propose an Artificial Intelligence (AI) based Question Answering (QA) system in order to automate patient prioritization. In more specific medical subarea like emergency departments (EDs), healthcare staff face major challenges such as managing patient prioritization and complex clinical decision-making. Our study focuses on the deployment of Deep Learning (DL) and transformer-based models in specific medical applications. Indeed, we simulated the reasoning process underlying the questions asked by healthcare professionals. We evaluated MLP, LSTM, TabNet and TabTransformer models on dataset constructed from informations provided in Tunisian hospital. The proposed system effectiveness is assessed using various metrics. Results showed that TabNet-based model outperforms others with an R2 of 0.9997 and an MSE of 0.0004.
Touati et al. (Thu,) studied this question.