{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T09:50:40Z","timestamp":1782467440849,"version":"3.54.5"},"reference-count":36,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:00:00Z","timestamp":1780876800000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["PCN Reports"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>This study aimed to classify patients with bipolar disorder (BD) and normal controls (NCs) using machine\u2010learning models that incorporate wearable\u2010derived core body temperature (CBT) and actigraphy\u2010derived sleep indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We enrolled 23 euthymic patients with BD and 43 NCs. Sleep parameters were collected via wrist actigraphy for 14 days, and CBT was measured with a wearable device for 3 days to estimate the CBT nadir and its phase differences with sleep indices. Models were constructed with a base model using CBT\u2010 and sleep\u2010derived features, and an extended model that included sociodemographic variables. Features were standardized (StandardScaler), and classifiers (random forest, LightGBM, and XGBoost) were evaluated. Hyperparameters were optimized using cross\u2010validation within the training data. Performance was evaluated using repeated nested cross\u2010validation. SHapley Additive exPlanations (SHAP) values were computed in the extended model to quantify relative feature contributions to the model output.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In nested cross\u2010validation at the MaxF1 operating point, the mean area under the receiver operating characteristic curve (ROC\u2013AUC) was 0.771\u2009\u00b1\u20090.162 for the base model and 0.930\u2009\u00b1\u20090.050 for the extended model. In the extended model, SHAP suggested that total sleep time, wake time, and the wake time\u2013CBT nadir phase difference were features potentially associated with the model output.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In this small\u2010sample study, a classification approach combining wearable\u2010derived CBT indices and actigraphy\u2010based sleep parameters suggested preliminary discrimination between BD and NC. Further validation is warranted in larger cohorts with balanced background characteristics, including disorders requiring differential diagnosis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/pcn5.70359","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T09:34:13Z","timestamp":1780911253000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine\u2010learning classification of bipolar disorder incorporating wearable\u2010derived core body temperature and actigraphy\u2010derived sleep indices"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2032-3873","authenticated-orcid":false,"given":"Kazuhiro","family":"Kurihara","sequence":"first","affiliation":[{"name":"Department of Neuropsychiatry, Graduate School of Medicine University of the Ryukyus Ginowan Okinawa Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ayano","family":"Shiroma","sequence":"additional","affiliation":[{"name":"Department of Neuropsychiatry, Graduate School of Medicine University of the Ryukyus Ginowan Okinawa Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masaki","family":"Kamata","sequence":"additional","affiliation":[{"name":"Department of Neuropsychiatry, Graduate School of Medicine University of the Ryukyus Ginowan Okinawa Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naruyo","family":"Yoshimoto","sequence":"additional","affiliation":[{"name":"Department of Neuropsychiatry, Graduate School of Medicine University of the Ryukyus Ginowan Okinawa Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ayano","family":"Saso","sequence":"additional","affiliation":[{"name":"Department of Neuropsychiatry, Graduate School of Medicine University of the Ryukyus Ginowan Okinawa Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akiyoshi","family":"Shimura","sequence":"additional","affiliation":[{"name":"Department of Somnology Tokyo Medical University Shinjuku\u2010ku Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukiko","family":"Imai","sequence":"additional","affiliation":[{"name":"ACCELStars Inc. 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