This work has been retracted.
RETRACTED ARTICLE: AI-optimized GRU-based self-attention model for predictive diabetes staging in IoT healthcare 5.0
Year: 2025
Type: article
Abstract: In the Healthcare 5.0 environment, the IoT devices are used for collecting the users statics. Hence, IoT devices can be used for the early detection and staging of diabetes. However, due to the complex interrelationship among the healthcare feature-set it is difficult to do an accurate prediction. In this context, this paper presents self-attention GRU model for predictive diabetes detection. A GRU-based self-attention mechanism captures temporal dependencies and spatial features that improves the model performance. Finally, CNN with Batch Normalization and ReLU performs the final classification. Experimental results show that the model achieved 93.94% accuracy, 95.28% precision, 93.94% recall, and an AUC of 0.9697, outperforming GRU, LSTM, RNN, and transformer-based baselines.
Source: Scientific Reports
Institutions: Jiading District Central Hospital, Shanghai University of Medicine and Health Sciences, Asia University, China Medical University, Korea University, Symbiosis International University, Kyung Hee University, China Medical University Hospital, Ronin Institute, Princess Nourah bint Abdulrahman University, Northern Border University, Chandigarh University, University of Petroleum and Energy Studies, Hong Kong Metropolitan University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4417166289