Student Work(Dissertation)COMP9005 MSc Machine Learning in Medical Data: Auto-ML vs.Traditional ML

Student | Client Work(Dissertation)|COMP9005 AI in Medicine: Optimizing Patient Care with Machine Learning|University of Kent

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This MSc dissertation from University of Kent (Canterbury, England) explores machine learning applied to medical data. In this research, we analyze the efficiency of Auto-ML frameworks like Auto-Sklearn and Auto-WEKA compared to traditional ML models. 🚀
Machine Learning is transforming clinical diagnosis by automating medical data processing, disease prediction, and pattern recognition in patient datasets. This video provides insights into:
📌 Key Topics Covered:
✅ Machine Learning in Healthcare: Auto-ML vs. Traditional ML
✅ Predictive Analytics: Using AI for Disease Prediction & Patient Care
✅ Auto-Sklearn vs. Auto-WEKA: Comparative Analysis in Medical Data
✅ Data Preprocessing & Feature Engineering in Medical Datasets
✅ Challenges in Medical AI: Ethical & Practical Considerations

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