Imanbek B 1

1. A Hybrid Machine Learning Approach for High-Accuracy Energy Consumption Prediction Using Indoor Environmental Quality Sensors
2. Benchmarking Tabular Foundation Models for Total Volatile Fatty Acid Prediction in Anaerobic Digestion
3. IoT-Based Unsupervised Learning for Characterizing Laboratory Operational States to Improve Safety and Sustainability
4. Interpretable Machine Learning-Based Differential Diagnosis of Hip and Knee Osteoarthritis Using Routine Preoperative Clinical and Laboratory Data
5. Non-Imaging Differential Diagnosis of Lower Limb Osteoarthritis: An Interpretable Machine Learning Framework
6. A Review of Innovative Medical Rehabilitation Systems with Scalable AI-Assisted Platforms for Sensor-Based Recovery Monitoring
7. Analyzing the Application of Digital Twin Technology in Manufacturing Processes
8. Architecting the Orthopedical Clinical AI Pipeline: A Review of Integrating Foundation Models and FHIR for Agentic Clinical Assistants and Digital Twins
9. STUDY OF THE ELECTROMAGNETIC IMPACT OF THE OVERHEAD TRANSMISSION LINES OF 330 KV ON ECOLOGICAL SYSTEMS
10. Application of Fuzzy Neural Networks in Combustion Process Diagnostics
11. Neural Network-Based Analysis of Flame States in Pulverised Coal and Biomass Co-Combustion
12. Calculation of temperature data from an automatic solar heat supply system
13. A Wearable IoT-Based Measurement System for Real-Time Cardiovascular Risk Prediction Using Heart Rate Variability
14. Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health
15. Enhancing Cardiovascular Disease Classification with Routine Blood Tests Using an Explainable AI Approach
16. Explainable AI for Coronary Artery Disease Stratification Using Routine Clinical Data
17. Interpretable Machine Learning for Coronary Artery Disease Risk Stratification: A SHAP-Based Analysis
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