袩褍斜谢懈泻邪褑懈懈 邪胁褌芯褉邪
Imanbek, B.
袙褋械谐芯 锌褍斜谢懈泻邪褑懈泄
24
袥械褌 邪泻褌懈胁薪芯褋褌懈
6
孝懈锌芯胁 锌褍斜谢懈泻邪褑懈泄
3
2026 (5)
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2025 (11)
- Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health
- Assessment of the Impact of Air Quality on Rehabilitation Effectiveness Using an IoMT-Based HRV Monitoring System
- IoT-Based Unsupervised Learning for Characterizing Laboratory Operational States to Improve Safety and Sustainability
- Neural Network-Based Analysis of Flame States in Pulverised Coal and Biomass Co-Combustion
- Interpretable Machine Learning for Coronary Artery Disease Risk Stratification: A SHAP-Based Analysis
- Enhancing Cardiovascular Disease Classification with Routine Blood Tests Using an Explainable AI Approach
- A Review of Innovative Medical Rehabilitation Systems with Scalable AI-Assisted Platforms for Sensor-Based Recovery Monitoring
- A Hybrid Machine Learning Approach for High-Accuracy Energy Consumption Prediction Using Indoor Environmental Quality Sensors
- A Wearable IoT-Based Measurement System for Real-Time Cardiovascular Risk Prediction Using Heart Rate Variability
- Explainable AI for Coronary Artery Disease Stratification Using Routine Clinical Data
- Analyzing the Impact of Air Quality on Cognitive Skills Using Machine Learning in a Smart Building Environment