袗胁褌芯褉写褘遥 卸邪褉懈褟谢邪薪褘屑写邪褉褘
Amangeldy, B.
袘邪褉谢褘覜 卸邪褉懈褟谢邪薪褘屑写邪褉
28
袘械谢褋械薪写褨谢褨泻 卸褘谢写邪褉褘
6
袞邪褉懈褟谢邪薪褘屑 褌爷褉谢械褉褨
3
2026 (5)
- Interpretable Machine Learning-Based Differential Diagnosis of Hip and Knee Osteoarthritis Using Routine Preoperative Clinical and Laboratory Data
- Non-Imaging Differential Diagnosis of Lower Limb Osteoarthritis: An Interpretable Machine Learning Framework
- Explainable Machine Learning for Volatile Fatty Acid Soft-Sensing in Anaerobic Digestion: A Pilot Feasibility Study
- Benchmarking Tabular Foundation Models for Total Volatile Fatty Acid Prediction in Anaerobic Digestion
- Architecting the Orthopedical Clinical AI Pipeline: A Review of Integrating Foundation Models and FHIR for Agentic Clinical Assistants and Digital Twins
2025 (14)
- Temporal Analysis of Indoor Air Quality Parameters in Metro Systems: A Focus on Diurnal Changes
- Enhancing Cardiovascular Disease Classification with Routine Blood Tests Using an Explainable AI Approach
- A Review of Artificial Intelligence and Deep Learning Approaches for Resource Management in Smart Buildings
- A Pilot Study on Thermal Comfort in Young Adults: Context-Aware Classification Using Machine Learning and Multimodal Sensors
- Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health
- IoT-Based Unsupervised Learning for Characterizing Laboratory Operational States to Improve Safety and Sustainability
- AI-Powered Building Ecosystems: A Narrative Mapping Review on the Integration of Digital Twins and LLMs for Proactive Comfort, IEQ, and Energy Management
- A Low-Cost IoT Sensor and Preliminary Machine-Learning Feasibility Study for Monitoring In-Cabin Air Quality: A Pilot Case from Almaty
- Interpretable Machine Learning for Coronary Artery Disease Risk Stratification: A SHAP-Based Analysis
- Development of Software for Hydrometallurgical Calculation of Metal Extraction
- 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
- Predicting Industrial Copper Hydrometallurgy Output with Deep Learning Approach Using Data Augmentation
- Analyzing the Impact of Air Quality on Cognitive Skills Using Machine Learning in a Smart Building Environment
2024 (3)
- Analyzing the Application of Digital Twin Technology in Manufacturing Processes
- Integrating IoT and Machine Learning for Advanced Chemoresistive Sensor Development in Smart Lab Environments
- Integrating Machine Learning with Intelligent Control Systems for Flow Rate Forecasting in Oil Well Operations