An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease
Abstract
Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine learning methods based on imaging data have poor interpretability because it is usually unclear how they make their decisions. Explainable Boosting Machines (EBMs) are interpretable machine learning models based on the statistical framework of generalized additive modeling, but have so far only been used for tabular data. Therefore, we propose a framework that combines the strength of EBM with high-dimensional imaging data using deep learning-based feature extraction. The proposed framework is interpretable because it provides the importance of each feature. We validated the proposed framework on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, achieving accuracy of 0.883 and area-under-the-curve (AUC) of 0.970 on AD and control classification. Furthermore, we validated the proposed framework on an external testing set, achieving accuracy of 0.778 and AUC of 0.887 on AD and subjective cognitive decline (SCD) classification. The proposed framework significantly outperformed an EBM model using volume biomarkers instead of deep learning-based features, as well as an end-to-end convolutional neural network (CNN) with optimized architecture.
Authors 12
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Erasmus MC · Erasmus University Rotterdam
Affiliation as printed
Department of Radiology & Nuclear Medicine , Erasmus MC , Rotterdam , The Netherlands
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Erasmus MC · Erasmus University Rotterdam
Affiliation as printed
Department of Radiology & Nuclear Medicine , Erasmus MC , Rotterdam , The Netherlands
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Affiliation as printed
Department of Neurology , Erasmus MC , Rotterdam , The Netherlands
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Affiliation as printed
Department of Neurology , Erasmus MC , Rotterdam , The Netherlands
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University Medical Center Groningen
Affiliation as printed
Department of Neurology & Alzheimer Center , University Medical Center Groningen , Groningen , The Netherlands
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University Medical Center Utrecht
Affiliation as printed
Department of Neurology , UMC Utrecht Brain Center , University Medical Center Utrecht , Utrecht , The Netherlands
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Radboud University Medical Center · Alzheimer’s Disease Neuroimaging Initiative
Affiliation as printed
Radboud University Medical Center , Nijmegen , The Netherlands
the Alzheimer's Disease Neuroimaging Initiative , and on
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Huub A. M. Middelkoop Aachen Department of Neurology and Neuropsychology Institute of Psychology, Health Medical and Neuropsychology Unit
Leiden University · Leiden University Medical Center
Affiliation as printed
Department of Neurology & Neuropsychology , Leiden University Medical Center , Leiden , The Netherlands
Institute of Psychology, Health, Medical and Neuropsychology Unit , Leiden University , The Netherlands
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Amsterdam University Medical Centers
Affiliation as printed
Amsterdam University Medical Center , location VUmc , Amsterdam , The Netherlands
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Maastricht University Medical Centre · Maastricht University
Affiliation as printed
Alzheimer Center Limburg , School for Mental Health and Neuroscience (MHeNS) , Maastricht University Medical Center , Maastricht , The Netherlands
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Erasmus MC · Erasmus University Rotterdam
Affiliation as printed
Department of Radiology & Nuclear Medicine , Erasmus MC , Rotterdam , The Netherlands
behalf of the Parelsnoer Neurodegenerative Diseases study group
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Erasmus MC · Erasmus University Rotterdam
Affiliation as printed
Department of Radiology & Nuclear Medicine , Erasmus MC , Rotterdam , The Netherlands