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- W4232516613 abstract "The current state-of-the-art for automated machine learning is adopted to predict Alzheimer's disease (AD) by adopting variables such as Mini Mental State Examination score, estimated total intracranial volume and Atlas Scaling Factor. A macro-weighted average Area under the Response-operating Curve of 0.96 is achieved with a close-to-perfect AD detection score after incorporating the ensemble approach. Such predictive models shall serve to optimize risk stratification and management protocols for this enfeebling ailment." @default.
- W4232516613 created "2022-05-12" @default.
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- W4232516613 date "2021-09-10" @default.
- W4232516613 modified "2023-10-18" @default.
- W4232516613 title "Predicting Alzheimer's disease from Clinical Dementia Rating, Estimated total intracranial volume & Atlas Scaling Factor : Incorporating Ensemble approach into Automated Machine Learning" @default.
- W4232516613 doi "https://doi.org/10.31219/osf.io/tx2g6" @default.
- W4232516613 hasPublicationYear "2021" @default.
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