{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:50:53Z","timestamp":1791395453854,"version":"4.3.3"},"reference-count":38,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:00Z","timestamp":1790467200000},"content-version":"vor","delay-in-days":88,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["493623632"],"award-info":[{"award-number":["493623632"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alz &amp;amp; Dem Diag Ass &amp;amp; Dis Mo"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>INTRODUCTION<\/jats:title>\n                    <jats:p>The introduction of disease\u2010modifying Alzheimer's therapies requires complex, labor\u2010intensive patient screening. Cloud\u2010based large language models (LLMs) could support this task but are often unsuitable for routine care due to data protection constraints.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      We evaluated an on\u2010premises, open\u2010weights LLM (gpt\u2010oss\u2010120b) for automated extraction of therapy\u2010relevant variables for lecanemab eligibility from German memory clinic reports. In a two\u2010stage design, LLM\u2010based extraction prompts, a deterministic rule\u2010based extractor, and a shared downstream rule\u2010based classifier were optimized on a development set (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a097) and evaluated on an independent hold\u2010out set (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a099), with expert consensus as ground truth.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The LLM\u2010based pipeline achieved 94% accuracy and a Cohen's kappa of 0.90 on the hold\u2010out set, significantly surpassing the rule\u2010based comparator (80% accuracy) and demonstrating performance comparable to human experts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>A locally deployed, on\u2010premises LLM may assist eligibility screening as a triage support tool, potentially facilitating access to novel therapies without compromising patient data privacy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dad2.70495","type":"journal-article","created":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T14:50:41Z","timestamp":1790520641000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Locally deployed large language model for real\u2010world lecanemab eligibility pre\u2010screening"],"prefix":"10.1002","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4485-1929","authenticated-orcid":false,"given":"Carolin","family":"Miklitz","sequence":"first","affiliation":[{"name":"Department of Old Age Psychiatry and Cognitive Disorders University Hospital Bonn  Bonn Germany"},{"name":"German Center for Neurodegenerative Diseases (DZNE Bonn)  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maya","family":"Shrestha","sequence":"additional","affiliation":[{"name":"German Center for Neurodegenerative Diseases (DZNE Bonn)  Bonn Germany"},{"name":"Rhenish Friedrich Wilhelm University of Bonn  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wegner","family":"Philipp","sequence":"additional","affiliation":[{"name":"German Center for Neurodegenerative Diseases (DZNE Bonn)  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nils","family":"Henk","sequence":"additional","affiliation":[{"name":"Department of Old Age Psychiatry and Cognitive Disorders University Hospital Bonn  Bonn Germany"},{"name":"German Center for Neurodegenerative Diseases (DZNE Bonn)  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alois Martin","family":"Sprinkart","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology University Hospital Bonn  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfgang","family":"Block","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology University Hospital Bonn  Bonn Germany"},{"name":"Department of Diagnostic and Interventional Neuroradiology and Pediatric Neuroradiology University Hospital Bonn  Bonn Germany"},{"name":"Department of Radiotherapy and Radiation Oncology University Hospital Bonn  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian Alexander","family":"Luetkens","sequence":"additional","affiliation":[{"name":"Department of Diagnostic and Interventional Radiology University Hospital Bonn  Bonn 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