{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T06:00:02Z","timestamp":1790316002797,"version":"4.1.0"},"reference-count":69,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of University and Research","award":["J97G22000170005"],"award-info":[{"award-number":["J97G22000170005"]}]},{"name":"Italian Ministry of University and Research","award":["ECS00000041"],"award-info":[{"award-number":["ECS00000041"]}]}],"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>\n                      Blood-based biomarkers (BBMs) are promising tools to facilitate biological diagnosis of Alzheimer\u2019s Disease (AD). Establishing reliable cutoffs for BBMs represents a major issue for real-world implementation and the investigation of combined BBM approaches is limited. Our aim is to test different machine learning (ML) models for BBMs interpretation with respect to established gold-standard\n                      <jats:italic>in vivo<\/jats:italic>\n                      biomarkers, i.e., cerebrospinal fluid (CSF) biomarkers, to enhance their standalone and combined diagnostic value for AD.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We selected 434 patients who referred to Perugia University Hospital for perceived cognitive decline with available CSF A \u03b2 42\/40, pTau181 and tTau and plasma A\u03b242, A\u03b240, pTau217, pTau181 and NfL. Multiple unsupervised clustering algorithms for cutoff determination and supervised classification models were compared for the prediction of AD defined by a CSF A\n                      <jats:sup>+<\/jats:sup>\n                      \/T\n                      <jats:sup>+<\/jats:sup>\n                      profile.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Different unsupervised clustering models obtained cutoffs with high performances in predicting an AD CSF profile (accuracy &amp;gt; 0.85). Each combination of cutoffs was tested, the best ones achieving A\n                      <jats:sup>+<\/jats:sup>\n                      \/T\n                      <jats:sup>+<\/jats:sup>\n                      CSF profile prevalences &amp;gt; 0.9 in BBM-positive subgroups. The best supervised ML models achieved accuracies up to 0.88 in 10-fold cross-validation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Our results prove that clustering approaches can help in identifying reliable BBMs cutoffs for AD diagnosis even in the absence of CSF gold standard reference and that ML approaches combining multiple BBMs can strongly enhance their diagnostic accuracy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2026.1922577","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T05:33:32Z","timestamp":1790314412000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of unsupervised and supervised machine learning approaches to blood-based biomarkers of Alzheimer\u2019s disease in a memory clinic cohort"],"prefix":"10.3389","volume":"18","author":[{"given":"Edoardo Guido","family":"Torrigiani","sequence":"first","affiliation":[{"name":"Section of Neurology, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davide","family":"Cianca","sequence":"additional","affiliation":[{"name":"Department of Physics and Geology, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Gaetani","sequence":"additional","affiliation":[{"name":"Section of Neurology, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanna","family":"Nardi","sequence":"additional","affiliation":[{"name":"Section of Neurology, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Federico","family":"Paolini Paoletti","sequence":"additional","affiliation":[{"name":"Section of Neurology, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davide","family":"Chiasserini","sequence":"additional","affiliation":[{"name":"Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucilla","family":"Parnetti","sequence":"additional","affiliation":[{"name":"Section of Neurology, Department of Medicine and Surgery, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Gammaitoni","sequence":"additional","affiliation":[{"name":"Department of Physics and Geology, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor","family":"Neri","sequence":"additional","affiliation":[{"name":"Department of Physics and Geology, University of Perugia","place":["Perugia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Bellomo","sequence":"additional","affiliation":[{"name":"Department of Life Science, Health and Health Professions, Link Campus University","place":["Rome, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,25]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e14609","DOI":"10.1002\/alz.14609","article-title":"A head-to-head comparison of plasma biomarkers to detect Alzheimer\u2019s disease in a memory clinic","volume":"21","author":"Anastasi","year":"2025","journal-title":"Alzheimers Dement."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1515\/cclm-2023-1434","article-title":"Blood-Based Biomarkers in Alzheimer\u2019s Disease \u2013 Moving Towards a New Era of Diagnostics","volume":"62","author":"Arslan","year":"2024","journal-title":"Clin. 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