医学数据挖掘

Learn essential medical data mining techniques through a comprehensive course covering linear and non-linear regression models, Meta-analysis, predictive model evaluation, dimensionality reduction methods, classification models, and deep learning applications in healthcare. Master data preprocessing, various regression analyses including Logistic and Cox survival analysis, dose-response modeling, ROC analysis, clustering techniques, and advanced classification methods like K-nearest neighbors, Support Vector Machines, and Random Forests. Explore practical applications in clinical diagnostics, mRNA microarray classification, miRNA marker extraction, and deep learning implementations using CNN for genomics and RNN for time series analysis. Develop expertise in applying these statistical and machine learning methods to real medical data through hands-on practice and culminating in a final examination.