{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T06:51:09Z","timestamp":1791874269269,"version":"4.3.4"},"reference-count":66,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":8,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100018928","name":"Westlake University","doi-asserted-by":"publisher","award":["10318A992001"],"award-info":[{"award-number":["10318A992001"]}],"id":[{"id":"10.13039\/100018928","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brain and Behavior"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Menopause, a natural biological transition in the life of women, is often associated with significant psychological disturbances such as depression, anxiety, and stress. However, early identification and management of psychological disorders in menopausal women remain under\u2010addressed due to limited specialist access and a lack of systematic screening approaches.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to develop ensemble\u2010based machine learning (ML) models to classify intervention\u2010related clinical and psychological outcome patterns in menopausal women using clinical and questionnaire\u2010based data collected during a controlled intervention study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>\n                      Psychological and menopausal symptoms were assessed using standardized tools, including the Depression Anxiety Stress Scale\u201021 (DASS\u201021), modified Kupperman index (MKI), vaginal health index (VHI), and menopause symptoms treatment satisfaction questionnaire (MS\u2010TSQ). Statistical analyzes were performed using chi\u2010square tests and independent\n                      <jats:italic>t<\/jats:italic>\n                      \u2010tests to evaluate group differences. Three ensemble classifiers, random forest (RF), gradient boosting (GB), and AdaBoost (AB), were evaluated using repeated cross\u2010validation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Result<\/jats:title>\n                    <jats:p>Among these, the RF classifier achieved the best performance with a sensitivity of 93.3%, a specificity of 90.0%, an accuracy of 91.7%, a precision of 90.3%, and an F1\u2010score of 91.8%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These results indicate that ensemble ML models, particularly RF, can serve as effective supplementary tools for psychological disorder risk stratification in menopausal care, aiding clinicians in decision\u2010making. However, these models are intended to complement, not replace, clinical assessments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/brb3.71787","type":"journal-article","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T04:31:36Z","timestamp":1791606696000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Ensemble\u2010Based Machine Learning Models for Classifying Intervention\u2010Related Psychological Outcome Patterns in Menopausal Women Treated With\n                    <i>Pimpinella anisum<\/i>"],"prefix":"10.1002","volume":"16","author":[{"given":"Md Belal Bin","family":"Heyat","sequence":"first","affiliation":[{"name":"CenBRAIN Neurotech Center of Excellence, School of Engineering Westlake University  Hangzhou China"},{"name":"Integrated\u2010on\u2010Chips Brain\u2010Computer Interfaces Zhejiang Engineering Research Center Westlake University, Hangzhou  Zhejiang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arshiya","family":"Sultana","sequence":"additional","affiliation":[{"name":"Department of Amraze Niswan Wa Ilmul Qabalat, National Institute of Unani Medicine Ministry of AYUSH  Bengaluru India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Attiq Ur","family":"Rehman","sequence":"additional","affiliation":[{"name":"Department of Cyber Security, School of Cyber Science and Engineering Huazhong University of Science and Technology  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arfa","family":"Begum","sequence":"additional","affiliation":[{"name":"Department of Amraze Niswan Wa Ilmul Qabalat, National Institute of Unani Medicine Ministry of AYUSH  Bengaluru India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamad","family":"Sawan","sequence":"additional","affiliation":[{"name":"CenBRAIN Neurotech Center of Excellence, School of Engineering Westlake University  Hangzhou China"},{"name":"Integrated\u2010on\u2010Chips Brain\u2010Computer Interfaces Zhejiang Engineering Research Center Westlake University, Hangzhou  Zhejiang China"},{"name":"Electrical Engineering, Polytechnique Montreal  Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,9]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.5530\/pj.2018.3.66"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1552"},{"key":"e_1_2_9_4_1","first-page":"31","article-title":"Anisoon (Pimpinella anisum L.): A Review of Pharmacological Activities and Clinical Effects","volume":"12","author":"Ali K. 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