{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T06:11:36Z","timestamp":1790143896697,"version":"4.0.1"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"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. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The co-occurrence of allergic rhinitis (AR) and attention-deficit\/hyperactivity disorder (ADHD) presents significant clinical challenges in pediatrics, yet predictive tools capturing non-linear neuro-immune interactions are lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed an interpretable Extreme Gradient Boosting (XGBoost) model utilizing a hybrid feature selection pipeline on a cohort of 518 pediatric AR patients (255 with comorbid ADHD). Model performance was evaluated via an independent test set. Global and local interpretability was decoded using SHapley Additive exPlanations (SHAP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A parsimonious subset of six predictors was identified. The XGBoost model achieved superior discriminative capacity (AUC\u202f=\u202f0.878) compared to conventional linear baselines. SHAP topographical analysis revealed profound non-linear thresholds and uncovered a critical synergistic interaction: elevated ADHD risk was strongly correlated with patients presenting simultaneously severe allergic inflammation (Total IgE\u202f&amp;gt;\u202f250\u202fIU\/mL) and nutritional deficiency (Vitamin D\u202f&amp;lt;\u202f20\u202fng\/mL). Furthermore, Decision Curve Analysis (DCA) demonstrated substantial net clinical benefit for triage application.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We established a highly robust, interpretable machine learning algorithm capable of accurately stratifying ADHD risk among AR children. The identified neuro-immune synergistic phenotypes provide critical mechanistic insights and offer a practical decision-support tool for timely pediatric multidisciplinary interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1837156","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T05:49:30Z","timestamp":1790142570000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of an interpretable machine learning model for predicting ADHD comorbidity in children with allergic rhinitis: a SHAP-based analysis"],"prefix":"10.3389","volume":"14","author":[{"given":"Hexiu","family":"Yuan","sequence":"first","affiliation":[{"name":"Ganzhou Hospital-Nanfang Hospital, Southern Medical University (Ganzhou People\u2019s Hospital)","place":["Ganzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nengjing","family":"Wu","sequence":"additional","affiliation":[{"name":"First Affiliated Hospital of Gannan Medical University","place":["Ganzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1016\/j.anai.2024.12.022","article-title":"Metabolomic profiles in allergic rhinitis: a systematic review and meta-analysis","volume":"134","author":"Liu","year":"2025","journal-title":"Ann Allergy Asthma Immunol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"3377","DOI":"10.1038\/s41598-022-07232-1","article-title":"Two meta-analyses of the association between atopic diseases and core symptoms of attention deficit hyperactivity disorder","volume":"12","author":"Chuang","year":"2022","journal-title":"Sci 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