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Erratum to: A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer’s Disease Spectrum

[Journal of Alzheimer’s Disease, 85 (2021) 1639-1655, DOI 10.3233/JAD-210573]

https://content.iospress.com/articles/journal-of-alzheimers-disease/jad210573

On page 1640, the Methods section, the full text needs to be changed to comply with ADNI consortium requirements. The text was:

Data used in the preparation of this article were obtained from the ADNI database (http://adni.loni.usc.edu). ADNI is a public-private repository of clinical, imaging, genetic, and biochemical biomarker data obtained from North American subjects or patients (ADNI | Alzheimer’s Disease Neuroimaging Initiative). ADNI aims to identify the determinant processes leading to AD and diagnose pathological changes occurring at the earliest stage. All ADNI data collected at baseline were downloaded and managed with custom-made R-written codes.

The text should be:

Data used in the preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial MRI, positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of MCI and early AD.