Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort
Musto, Henry; Stamate, Daniel; Pu, Ida and Stahl, Daniel. 2023. 'Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort'. In: Computational Collective Intelligence. ICCCI 2023.. Budapest, Hungary 27–29 September 2023. [Conference or Workshop Item]
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Abstract or Description
The rise of Alzheimer’s Disease worldwide has prompted a search for efficient tools which can be used to predict deterioration in cognitive decline leading to dementia. In this paper, we explore the potential of survival machine learning as such a tool for building models capable of predicting not only deterioration but also the likely time to deterioration. We demonstrate good predictive ability (0.86 C-Index), lending support to its use in clinical investigation and prediction of Alzheimer’s Disease risk.
Item Type: |
Conference or Workshop Item (Paper) |
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Identification Number (DOI): |
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Keywords: |
Survival Machine Learning, ADNI, Clinical Prediction Modelling |
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Dates: |
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Event Location: |
Budapest, Hungary |
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Date range: |
27–29 September 2023 |
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Item ID: |
35866 |
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Date Deposited: |
15 Apr 2024 09:34 |
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Last Modified: |
13 Sep 2024 01:26 |
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URI: |
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