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Although plasma\u2010based biomarkers such as amyloid\u2010\u03b2 (A\u03b2) and phosphorylated tau (p\u2010tau) have shown promise as diagnostic indicators, current single\u2010biomarker detection techniques lack the requisite sensitivity and specificity for early\u2010stage diagnosis. Here, we present the development of an\n                    <jats:styled-content>u<\/jats:styled-content>\n                    ltrasensitive\n                    <jats:styled-content>C<\/jats:styled-content>\n                    RISPR\u2010based\n                    <jats:styled-content>m<\/jats:styled-content>\n                    ulti\u2010protein\n                    <jats:styled-content>d<\/jats:styled-content>\n                    etection\n                    <jats:styled-content>a<\/jats:styled-content>\n                    rray (UCMDA) capable of concurrently detecting six core AD biomarkers, including A\u03b2\n                    <jats:sub>40<\/jats:sub>\n                    , A\u03b2\n                    <jats:sub>42<\/jats:sub>\n                    , p\u2010tau\n                    <jats:sup>181<\/jats:sup>\n                    , p\u2010tau\n                    <jats:sup>217<\/jats:sup>\n                    , p\u2010tau\n                    <jats:sup>231<\/jats:sup>\n                    , and p\u2010tau\n                    <jats:sup>396,404<\/jats:sup>\n                    . By integrating antibody pair\u2010based multiplex recombinase polymerase amplification (RPA) with spatially encoded CRISPR\u2010Cas12a detection, the UCMDA achieves a detection limit of 1 fg\/mL, which is 10\u00a0000\u2010fold more sensitive than conventional ELISA. Clinical validation in a cohort of 155 plasma samples demonstrated that logistic regression (LR)\u2010based integration of the six biomarkers significantly enhanced diagnostic performance, with the multi\u2010biomarker model substantially outperforming single\u2010biomarker approaches in diagnosing AD\u2010MCI and AD. This platform offers a scalable, cost\u2010effective, and minimally invasive strategy for early detection and disease monitoring. This work highlights the potential of CRISPR\u2010based multiplex protein detection technologies combined with machine learning\u2010assisted analysis to enhance the precision of diagnosing neurodegenerative disorders.\n                  <\/jats:p>","DOI":"10.1002\/advs.75983","type":"journal-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T10:01:38Z","timestamp":1780999298000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Machine Learning\u2010Enhanced Ultrasensitive Immuno\u2010CRISPR Array Facilitates Early Diagnosis of Alzheimer's Disease by Detecting Multiple Plasma Biomarkers"],"prefix":"10.1002","volume":"13","author":[{"given":"Liding","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical Engineering Hainan University  Haikou 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Hainan University  Haikou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6076-7711","authenticated-orcid":false,"given":"Yaoqiang","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute of Basic and Clinical Medicine The First People's Hospital of Yunnan  Kunming China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Can","family":"Sheng","sequence":"additional","affiliation":[{"name":"Department of Neurology the Affiliated Hospital of Jining Medical University  Jining China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2836-1217","authenticated-orcid":false,"given":"Ming","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Renmin Hospital of Wuhan University  Wuhan 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