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https://github.com/riborings/alzheimerprediction


https://github.com/riborings/alzheimerprediction

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# AlzheimerPrediction

The primary objective of our project was to predict binary-coded CDR scores in both cross-sectional and longitudinal contexts. Initially, we conducted a joint analysis of OASIS-I and OASIS-II, binarised CDR, and preprocessed input features. Subsequently, we selected and optimised a logistic regression classifier for cross-sectional prediction, achieving balanced accuracies of 80.7% and 78.6% with and without MMSE as a feature, respectively. Finally, we designed and trained an LSTM model that predicted the CDR outcome longitudinally with a balanced accuracy of 80%.