{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T13:23:19Z","timestamp":1790083399155,"version":"4.0.1"},"reference-count":34,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000024","name":"Canadian Institute of Health Research","doi-asserted-by":"crossref","award":["PJT-173540"],"award-info":[{"award-number":["PJT-173540"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Krembil-Rossy Chair Program"},{"name":"Queen Elizabeth II Graduate Scholarship in Science & Technology"},{"name":"Krembil Brain Institute","award":["NA"],"award-info":[{"award-number":["NA"]}]},{"name":"University of Toronto School of Graduate Studies","award":["NA"],"award-info":[{"award-number":["NA"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Parkinson\u2019s disease is a movement disorder featuring motor symptoms and cognitive decline, which can manifest as mild cognitive impairment. The incidence of mild cognitive impairment increases with disease progression, and Parkinson\u2019s disease can cause significant disability, therefore, identification of Parkinson\u2019s disease and mild cognitive impairment in Parkinson\u2019s disease is imperative. Neuroimaging and biofluid biomarkers have been studied separately, however, research suggests that combining biomarkers may improve detection.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>We aimed to investigate using machine learning whether a combination of neuroimaging and biofluid biomarkers would result in more effective identification of Parkinson\u2019s disease and mild cognitive impairment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Utilizing the Parkinson\u2019s Progression Markers Initiative dataset, we applied two different machine learning approaches, support vector machine and random forest, to explore combinations of neuroimaging and cerebrospinal fluid biomarkers for detection.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Overall, both machine learning techniques had an equivalent performance. In general, in those models for detecting Parkinson\u2019s disease, DaT-SPECT performed better than biofluid biomarkers. In models for detecting Parkinson\u2019s disease patients with mild cognitive impairment, combining DaT-SPECT with phosphorylated-tau-181 resulted in higher accuracy, outperforming DaT-SPECT alone.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec005\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Classification for Parkinson\u2019s disease and mild cognitive impairment may be improved by combining neuroimaging with biofluid biomarkers through machine learning models.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0335541","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T18:22:56Z","timestamp":1763576576000},"page":"e0335541","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Using machine learning for detection of Parkinson\u2019s disease and mild cognitive 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