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大流行的爆发表明,在医疗人员和设备短缺加剧的情况下,及时干预至关重要; 疼痛程度筛查是确定病人病情严重程度的第一步; 自动确认病情有助于确定病人的症状,以便立即采取适当行动,提供适合病人状况的以病人为中心的医疗计划; 在本文件中,我们提出了一个用于在阿拉伯联合酋长国部署的疼痛程度检测框架,并使用文献中最常用的方法评估其表现; 我们的结果表明,采用疼痛程度深度学习检测框架对于准确确定疼痛程度很有希望。</s>