{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T07:01:54Z","timestamp":1775804514874,"version":"3.50.1"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Receiving timely Alzheimer\u2019s disease (AD) diagnosis is often delayed due to long waitlists for specialists. Our study aimed to bridge the gap between the timeliness and complexity of diagnosing AD by developing a scoring system with interpretable machine learning using variables that are obtainable at integrated primary care settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We trained the model using 666 participants with normal cognition or mild cognitive impairment at baseline visit from the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) and externally validated the scorecard using 4,876 participants from the National Alzheimer\u2019s Coordinating Center (NACC). We integrated cognitive measures, daily functioning measured with Functional Assessment Questionnaire (FAQ), and demographics into FasterRisk algorithm.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Combinations of 4 separate measures were selected to generate 10 scorecards, showing strong performance (area under the curve [AUC]\u202f=\u202f0.868\u20130.892) in ADNI and remaining robust when externally validated in NACC (AUC\u202f=\u202f0.795). The features were Category Animal \u2264 20 (2 points), Trail Making Test B\u202f\u2264\u202f143 (\u22123 points), Logical Memory Delayed \u2264 3 (4 points), Logical Memory Delayed \u2264 8 (3 points), and FAQ\u202f\u2264\u202f2 (\u22125 points). The probable AD risk increased correspondingly with higher total points: 7.4% (\u22128), 25.3% (\u22124), 50% (\u22121), 74.7% (2), and &amp;gt;90% (&amp;gt;6). We refer to this model as the (F)unctioning, (LA)nguage, (M)emory, and (E)xecutive functioning or FLAME scorecard.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation<\/jats:title>\n                    <jats:p>Our findings highlight the potential to predict AD development using obtainable information, allowing for implementation into integrated primary care workflows to initiate early intervention. While our scope centers on AD, this established foundation paves the way for other types of dementia.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2026.1759273","type":"journal-article","created":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T06:06:54Z","timestamp":1775801214000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of Alzheimer\u2019s disease risk score for future integrated primary care: a white-box approach"],"prefix":"10.3389","volume":"18","author":[{"given":"Yumiko","family":"Wiranto","sequence":"first","affiliation":[{"name":"Department of Psychology, University of Kansas","place":["Lawrence, KS, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Devin","family":"Setiawan","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, University of Kansas","place":["Lawrence, KS, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amber","family":"Watts","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Kansas","place":["Lawrence, KS, United States"]},{"name":"Alzheimer\u2019s Disease Research Center, University of Kansas","place":["Fairway, KS, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arian","family":"Ashourvan","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Kansas","place":["Lawrence, KS, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1097\/WAD.0b013e318142774e","article-title":"The national Alzheimer\u2019s coordinating center (NACC) database: the uniform data set","volume":"21","author":"Beekly","year":"2007","journal-title":"Alzheimer Dis. 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