Data Collection: Gathering relevant clinical and demographic data. Preprocessing: Cleaning the data to remove missing or inconsistent information. Feature Selection: Identifying the most significant variables that influence the outcome. Model Training: Using the selected features to train the LDA model. Classification: Applying the model to classify new data into predefined categories.
