The outbreak of the COVID-19 pandemic revealed the criticality of timely intervention in a situation exacerbated by a shortage in medical staff and equipment. Pain-level screening is the initial step toward identifying the severity of patient conditions. Automatic recognition of state and feelings help in identifying patient symptoms to take immediate adequate action and providing a patient-centric medical plan tailored to a patient's state. In this paper, we propose a framework for pain-level detection for deployment in the United Arab Emirates and assess its performance using the most used approaches in the literature. Our results show that a deployment of a pain-level deep learning detection framework is promising in identifying the pain level accurately.

翻译：COVID-19疫情的爆发揭示了在医疗人员和设备短缺加剧的背景下及时干预的关键性。疼痛等级筛查是识别患者病情严重程度的首要步骤。自动识别状态和情感有助于判断患者症状，以便立即采取适当措施，并制定以患者为中心的个性化医疗方案。本文提出了一种适用于阿拉伯联合酋长国部署的疼痛等级检测框架，并使用文献中最常用的方法评估其性能。结果表明，部署深度学习疼痛等级检测框架在准确识别疼痛等级方面具有良好前景。