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Authors
Jones, D. https://orcid.org/0000-0002-4807-9833
Lowe, V.
Graff-Radford, J.
Botha, H. https://orcid.org/0000-0003-4390-685X
Barnard, L.
Wiepert, D.
Murphy, M. C.
Murray, M. https://orcid.org/0000-0001-7379-2545
Senjem, M. https://orcid.org/0000-0001-9308-9275
Gunter, J.
Wiste, H.
Boeve, B. https://orcid.org/0000-0002-4153-8187
Knopman, D. https://orcid.org/0000-0002-6544-066X
Petersen, R.
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Funding
Funding for this research was provided by:
U.S. Department of Health & Human Services | National Institutes of Health (P30 AG62677, P50 AG016574)
U.S. Department of Health & Human Services | National Institutes of Health
U.S. Department of Health & Human Services | NIH | National Institute on Aging (U01 AG06786, R01 AG011378, R01 AG041851)
U.S. Department of Health & Human Services | NIH | National Institute on Aging
U.S. Department of Health & Human Services | NIH | National Institute on Aging
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Article History
Received: 21 October 2020
Accepted: 17 February 2022
First Online: 28 March 2022
Competing interests
: D.J. is an inventor on a patent application describing existing machine learning techniques for automated clinical readings of medical images including brain FDG-PET images for evaluating neurogenerative dementia syndromes (Applicant: Mayo Foundation for Medical Education and Research; Inventor: David T. Jones; Provisional Application: 62/693,267; US National Application: 17/254,542; Status: Pending). The machine learning techniques in this study are not linked to this patent application. The remaining authors declare no competing interests.
