{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T17:20:38Z","timestamp":1777396838277,"version":"3.51.4"},"reference-count":43,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["06500103"],"award-info":[{"award-number":["06500103"]}]},{"name":"the Liaoning Province Science and Technology Joint Project","award":["2024-MSLH-072"],"award-info":[{"award-number":["2024-MSLH-072"]}]},{"name":"the Dalian High-Level Talents Innovation Support Plan","award":["2021RQ029 and 2023RY019"],"award-info":[{"award-number":["2021RQ029 and 2023RY019"]}]},{"name":"the Dalian Medical Key Specialty \u201cClimbing the Peak Plan\u201d","award":["2022ZZ267 and 2023ZZ012"],"award-info":[{"award-number":["2022ZZ267 and 2023ZZ012"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Dementia, a progressive neurological disorder, is a leading cause of disability and death globally, often underdiagnosed in its early stages. Early diagnosis, prevention, and treatment are crucial for mitigating its impact on individuals and society.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to predict the exact conversion time from normal cognition (NC) to mild cognitive impairment (MCI), and to provide insights for early diagnosis and treatment of dementia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A novel dual attention convolutional network model was proposed to handle high-dimensional features and limited patients\u2019 records in short-sequence time series data. It integrated feature and temporal attention modules to capture dependencies and used a custom loss function to enhance clinical interpretability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The model significantly reduced mean squared error (MSE) by 9.67% and mean absolute error (MAE) by 26.24%, while increasing the r-square (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                          <mml:msup>\n                            <mml:mrow>\n                              <mml:mi mathvariant=\"normal\">R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mn>2<\/mml:mn>\n                          <\/mml:msup>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ) by 16.71% compared to a basic convolutional model. It effectively predicted NC to MCI conversion, offering valuable guidance for early intervention.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The dual attention convolutional network model effectively predicted NC to MCI conversion, providing a valuable tool for early dementia diagnosis and treatment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13872877251386078","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T17:20:40Z","timestamp":1760721640000},"page":"1115-1131","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting the conversion time from normal cognition to mild cognitive impairment based on dual attention convolutional networks"],"prefix":"10.1177","volume":"108","author":[{"given":"Xiawei","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Haidian District, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5336-0200","authenticated-orcid":false,"given":"Sibo","family":"Liu","sequence":"additional","affiliation":[{"name":"Intensive Care Unit, Central Hospital of Dalian University of Technology, Shahekou District, Dalian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Haidian District, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinjie","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Central Hospital of Dalian University of Technology, Shahekou District, Dalian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dean","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Qingdao Central Hospital, University of Health and Rehabilitation Science (Qingdao Central Hospital), Shibei District, Qingdao, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8012-3697","authenticated-orcid":false,"given":"Chao","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Haidian District, Beijing, China"},{"name":"Shunde Innovation School, University of Science and Technology Beijing, Foshan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"Global action plan on the public health response to dementia 2017\u20132025","author":"World Health Organization","year":"2017","unstructured":"World Health Organization. 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