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InfoResearchPeer-reviewed
Reinforcement Learning-Enhanced Dynamic LSTM Training With Meta-Feature Extraction for Small Time-Series VOC Datasets in CKD Detection
- Published
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Summary
This study proposes an AI-based framework that identifies disease-specific volatile organic compounds (VOCs) in exhaled breath for noninvasive early detection. It combines deep learning and reinforcement learning to improve accuracy and reliability on small datasets. The authors name ammonia as especially elevated in chronic kidney disease (CKD).