{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T16:05:23Z","timestamp":1788451523749,"version":"build-2803163510"},"reference-count":78,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BioTech"],"abstract":"<jats:p>Systemic lupus erythematosus (SLE) is a complex autoimmune disease that poses serious long-term patient burdens. (1) Background: SLE patient classification and care are often complicated by case heterogeneity (diverse variations in symptoms and severity). Large language models (LLMs) and generative artificial intelligence (genAI) may mitigate this challenge by profiling medical records to assess key medical criteria. (2) Methods: To demonstrate genAI-based profiling, ACR (American College of Rheumatology) 1997 SLE classification criteria were used to define medically relevant LLM prompts. Records from 78 previously studied patients (45 classified as having SLE; 33 indeterminate or negative) were computationally profiled, via five genAI replicate runs. (3) Results: GenAI determinations of the \u201cDiscoid Rash\u201d and \u201cPleuritis or Pericarditis\u201d classification criteria yielded perfect concurrence with clinical classification, while some factors such as \u201cImmunologic Disorder\u201d (56% accuracy) were statistically unreliable. Compared to clinical classification, our genAI approach achieved a 72% predictive success rate. (4) Conclusions: GenAI classifications may prove sufficiently predictive to aid medical professionals in evaluating SLE patients and structuring care strategies. For individual criteria, accuracy seems to correlate inversely with complexities in clinical determination, implying that improvements in AI patient profiling tools may emerge from continued advances in clinical classification efficacy.<\/jats:p>","DOI":"10.3390\/biotech14010015","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T04:55:08Z","timestamp":1741236908000},"page":"15","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Prediction of Lupus Classification Criteria via Generative AI Medical Record Profiling"],"prefix":"10.3390","volume":"14","author":[{"given":"Sandeep","family":"Nair","sequence":"first","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5821-4253","authenticated-orcid":false,"given":"Gerald H.","family":"Lushington","sequence":"additional","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohan","family":"Purushothaman","sequence":"additional","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernard","family":"Rubin","sequence":"additional","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6868-4742","authenticated-orcid":false,"given":"Eldon","family":"Jupe","sequence":"additional","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santosh","family":"Gattam","sequence":"additional","affiliation":[{"name":"Progentec Diagnostics, Inc., 755 Research Pkwy, Oklahoma City, OK 73104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e031850","DOI":"10.1136\/bmjopen-2019-031850","article-title":"Association between organ damage and mortality in systemic lupus erythematosus: A systematic review and meta-analysis","volume":"10","author":"Lin","year":"2020","journal-title":"BMJ Open"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1002\/art.41632","article-title":"Prevalence of Systemic Lupus Erythematosus in the United States: Estimates from a Meta-Analysis of the Centers for Disease Control and Prevention National Lupus Registries","volume":"73","author":"Izmirly","year":"2021","journal-title":"Arthritis Rheumatol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/13696998.2019.1678170","article-title":"Real-world medication use and economic outcomes in incident systemic lupus erythematosus patients in the United States","volume":"23","author":"Kariburyo","year":"2020","journal-title":"J. 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