Evidence map›Paper›PMID 40257111›Full record

ArticleAmerican journal of Alzheimer's disease and other dementias

Alzheimer's Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis.

Abolfazl Mollalo, George Grekousis, Hermes Florez, Brian Neelon, Leslie A Lenert, Alexander V Alekseyenko

Abstract read
In one paragraph

Article in American journal of Alzheimer's disease and other dementias. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Abolfazl MollaloDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.ORCID 0000-0001-5092-0698
George GrekousisSchool of Geography and Planning, Department of Urban and Regional Planning, Sun Yat-Sen University, Guangzhou, China.
Hermes FlorezDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Brian NeelonDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Leslie A LenertDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Alexander V AlekseyenkoDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.

Funding

South Carolina Cancer Disparities Research Center (SC CADRE)U54CA210962 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI FORD, MARVELLA ELIZABETH, SALLEY, JUDITH · 2017 to 2023
$6.7M
NCI NIH HHS U54 CA210962
6 · The paper itself

Abstract

A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer's disease (AD) dementia, yet the spatial variability and relative importance of the most influential factors remain underexplored. We compiled various widely recognized factors to examine spatial heterogeneity and associations with AD dementia prevalence via geographically weighted random forest (GWRF) approach. The GWRF outperformed conventional models with an out-of-bag R

Indexed as

Alzheimer DiseaseMachine LearningNeighborhood CharacteristicsHumansPrevalenceRisk FactorsSpatial AnalysisUnited StatesAlzheimer's Disease dementiageographically weighted random forestgeographic information systems (GIS)neighborhood characteristicsspatial machine learning

Identifiers

PMID40257111
PMCPMC12035167

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.