Faculty Of Information Technologies And Artificial Intelligence 1

1. Benchmarking Tabular Foundation Models for Total Volatile Fatty Acid Prediction in Anaerobic Digestion
2. IoT-Based Unsupervised Learning for Characterizing Laboratory Operational States to Improve Safety and Sustainability
3. A Lightweight, End-to-End Encrypted Data Pipeline for IIoT: An AES-GCM Implementation for ESP32, MQTT, and Raspberry Pi
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. Architecting the Orthopedical Clinical AI Pipeline: A Review of Integrating Foundation Models and FHIR for Agentic Clinical Assistants and Digital Twins
7. Interpretable Diagnosis of Pulmonary Emphysema on Low-Dose CT Using ResNet Embeddings
8. A Wearable IoT-Based Measurement System for Real-Time Cardiovascular Risk Prediction Using Heart Rate Variability
9. Enhancing Cardiovascular Disease Classification with Routine Blood Tests Using an Explainable AI Approach
10. Explainable AI for Coronary Artery Disease Stratification Using Routine Clinical Data
11. Interpretable Machine Learning for Coronary Artery Disease Risk Stratification: A SHAP-Based Analysis
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