Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Disentangling Alzheimer's disease neurodegeneration from typical brain
  aging using machine learning   Neuroimaging biomarkers that distinguish between typical brain aging and
Alzheimer's disease (AD) are valuable for determining how much each contributes
to cognitive decline. Machine learning models can derive multi-variate brain
change patterns related to the two processes, including the SPARE-AD (Spatial
Patterns of Atrophy for Recognition of Alzheimer's Disease) and SPARE-BA (of
Brain Aging) investigated herein. However, substantial overlap between brain
regions affected in the two processes confounds measuring them independently.
We present a methodology toward disentangling the two. T1-weighted MRI images
of 4,054 participants (48-95 years) with AD, mild cognitive impairment (MCI),
or cognitively normal (CN) diagnoses from the iSTAGING (Imaging-based
coordinate SysTem for AGIng and NeurodeGenerative diseases) consortium were
analyzed. First, a subset of AD patients and CN adults were selected based
purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN
individuals) and SPARE-AD1 (classification of CN versus AD). Second, analogous
groups were selected based on clinical and molecular markers to train SPARE-BA2
and SPARE-AD2: amyloid-positive (A+) AD continuum group (consisting of A+AD,
A+MCI, and A+ and tau-positive CN individuals) and amyloid-negative (A-) CN
group. Finally, the combined group of the AD continuum and A-/CN individuals
was used to train SPARE-BA3, with the intention to estimate brain age
regardless of AD-related brain changes. Disentangled SPARE models derived brain
patterns that were more specific to the two types of the brain changes.
Correlation between the SPARE-BA and SPARE-AD was significantly reduced.
Correlation of disentangled SPARE-AD was non-inferior to the molecular
measurements and to the number of APOE4 alleles, but was less to AD-related
psychometric test scores, suggesting contribution of advanced brain aging to
these scores.

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The categories of this paper are: hep-th
18
The categories of this paper are: econ
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The categories of this paper are: eess
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
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The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org