Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 339-347 |
| Number of pages | 9 |
| Journal | Procedia Computer Science |
| Volume | 220 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 14th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023 - Leuven, Belgium Duration: Mar 15 2023 → Mar 17 2023 |
Keywords
- Computer Vision
- Deep Learning
- eHealth
- Image Processing
- Machine Learning
- Pain Detection
- Patient-Centric
- Smart healthcare
ASJC Scopus subject areas
- Computer Science(all)