{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T05:10:41Z","timestamp":1779253841435,"version":"3.51.4"},"reference-count":19,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:00:00Z","timestamp":1779235200000},"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. Mol. Biosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Tuberculosis (TB) treatment response prediction is critical for personalized care. We developed an ensemble Transformer framework integrating clinical and transcriptomic data from 467 patients and five GEO datasets (GSE83456, GSE107995, GSE158802, GSE19435, GSE25534).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Five diverse Transformer architectures were trained with Focal Loss, label smoothing, and stratified 5-fold cross-validation. Outcome labels were harmonized using sputum culture conversion at 2 months.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The model achieved 97.1% accuracy and AUC 0.949 [95% CI: 0.912\u20130.978] on independent test folds, with sensitivity and specificity both 95%. Bootstrap validation (n = 1000) confirmed robustness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This framework provides a clinically-relevant tool for TB treatment response prediction, pending prospective validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical Trial Registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/www.chictr.org.cn\/<\/jats:ext-link>\n                      , identifier ChiCTR2300074328 03\/08\/2023.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmolb.2026.1788211","type":"journal-article","created":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T04:45:30Z","timestamp":1779252330000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Transformer-based ensemble framework for tuberculosis treatment response prediction: multi-omics integration with clinical-grade performance"],"prefix":"10.3389","volume":"13","author":[{"given":"Huanhuan","family":"Ba","sequence":"first","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huanqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Information Management Office, Northwestern Polytechnical University","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"Drug Clinical Trial Institution Office, Xi\u2019an Chest Hospital","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, The Eighth\u2019s Hospital of Xi\u2019an","place":["Xi\u2019an, Shaanxi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1038\/nature09247","article-title":"An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis","volume":"466","author":"Berry","year":"2010","journal-title":"Nature"},{"key":"B3","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1038\/s41576-019-0122-6","article-title":"Deep learning: new computational modelling techniques for genomics","volume":"20","author":"Eraslan","year":"2019","journal-title":"Nat. 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