ArticleProcedia computer science2023
Towards a Deep Learning Pain-Level Detection Deployment at UAE for Patient-Centric-Pain Management and Diagnosis Support: Framework and Performance Evaluation.
Article in Procedia computer science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of AI in Multilevel Pain Assessment Using Facial Images: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- A Public Health Approach to Automated Pain Intensity Recognition in Chest Pain Patients via Facial Expression Analysis for Emergency Care Prioritization.Diagnostics (Basel, Switzerland) · 2025Article
- A Multimodal Pain Sentiment Analysis System Using Ensembled Deep Learning Approaches for IoT-Enabled Healthcare Framework.Sensors (Basel, Switzerland) · 2025Article
- Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.PloS one · 2024Article
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2 authors.
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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.
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