{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T14:18:41Z","timestamp":1774707521191,"version":"3.50.1"},"reference-count":62,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013078","name":"Natural Science Research Project of Guizhou Province","doi-asserted-by":"publisher","award":["MS(2025) 626"],"award-info":[{"award-number":["MS(2025) 626"]}],"id":[{"id":"10.13039\/501100013078","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>\n                    The application of artificial intelligence\u2010assisted diagnosis technology in the field of medical imaging is becoming increasingly in\u2010depth. The pathological diagnosis of bone tumors is a very time\u2010consuming and error\u2010prone task. However, the existing models still face problems such as loss of semantic information when processing pathological images of bone tumors, resulting in inaccurate recognition. This leads to proposing a tumor\u2010assisted prediction strategy (MCFFS) based on multi\u2010scale feature fusion to achieve accurate segmentation and grade recognition. It introduces the Swin structure to replace the downsampling and upsampling processes in the traditional U\u2010Net to achieve the fusion of deep and shallow feature information at different levels; by constructing a multiscale feature fusion strategy based on transformer to enhance the fusion of low\u2010 and high\u2010dimensional spatial information; through the prediction algorithm with weight update, accurate classification of pathological images is achieved. The segmentation Dice Similariy Coefficient (DSC) of the MCFFS method reached 0.849, and the classification accuracy reached 0.938, indicating that it has superior performance in cell nucleus segmentation and tumor classification prediction, providing a strong auxiliary reference for doctors' clinical diagnosis. Code:\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/GFF1228\/MCFFS.git\">https:\/\/github.com\/GFF1228\/MCFFS.git<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1002\/aisy.202500455","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T22:24:36Z","timestamp":1751581476000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Tumor Auxiliary Prediction Strategy Based on Multiscale Feature Fusion in Medical Decision\u2010Making System"],"prefix":"10.1002","volume":"7","author":[{"given":"Yingqing","family":"Lu","sequence":"first","affiliation":[{"name":"Department of Anesthesiology Xiangya Hospital, Central South University  Changsha P. R. China"},{"name":"National Clinical Research Center for Geriatric Disorders Xiangya Hospital, Central South University  Changsha P. R. China"}]},{"given":"Jing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Hunan University of Medicine General Hospital  Huaihua 418000 P. R. China"}]},{"given":"Fangfang","family":"Gou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University  Guiyang 550025 P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9013-0818","authenticated-orcid":false,"given":"Jia","family":"Wu","sequence":"additional","affiliation":[{"name":"National Pilot School of Software Yunnan Key Laboratory of Software Engineering Yunnan University  Kunming P. R. China"},{"name":"Research Center for Artificial Intelligence Monash University  Melbourne, Clayton VIC 3800 Australia"}]}],"member":"311","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106405"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2024.111000"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00256-024-04621-7"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12941"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12943-024-02105-9"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2024.3351287"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.7150\/thno.77949"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.106439"},{"key":"e_1_2_8_10_1","doi-asserted-by":"crossref","unstructured":"F.Du P.Yang Q.Jia F.Nan X.Chen Y.Yang inIn Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition2023 pp.15814\u201315823.","DOI":"10.1109\/CVPR52729.2023.01518"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3381239"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.10.030"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-024-01471-7"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3445969"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3429340"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3432531"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3431916"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-024-01479-z"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3436608"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14141472"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2024.109493"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-024-01660-4"},{"key":"e_1_2_8_23_1","first-page":"1","author":"Aburass S.","year":"2025","journal-title":"Journal of Imaging Informatics in Medicine"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105814"},{"key":"e_1_2_8_25_1","doi-asserted-by":"crossref","unstructured":"M.Zhao J.Fang B.Chen IEEE J. Biomed. Health Inform. https:\/\/doi.org\/10.1109\/JBHI.2025.3548696.","DOI":"10.1109\/JBHI.2025.3548696"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3435714"},{"key":"e_1_2_8_27_1","doi-asserted-by":"crossref","unstructured":"G.Lv K.Wen Z.Wu X.Jin H.An J.He \u201cNuclei R\u2010CNN: Improve Mask R\u2010CNN for Nuclei Segmentation \u201d2019 IEEE 2nd Inter. Conf. on Information Communication and Signal Processing (ICICSP) Weihai China2019 pp.357\u2013362 https:\/\/doi.org\/10.1109\/ICICSP48821.2019.8958541.","DOI":"10.1109\/ICICSP48821.2019.8958541"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1088\/2057-1976\/ad89c7"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3289224"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.3390\/app13179802"},{"key":"e_1_2_8_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22949"},{"key":"e_1_2_8_32_1","doi-asserted-by":"crossref","unstructured":"L.Krishnakumari R.Ramalakshmi V.Srirenganachiyar K.Ragavan K.Ramalakshmi 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS) Coimbatore India2023 pp.665\u2013668 https:\/\/doi.org\/10.1109\/ICAIS56108.2023.10073676.","DOI":"10.1109\/ICAIS56108.2023.10073676"},{"key":"e_1_2_8_33_1","doi-asserted-by":"crossref","unstructured":"Y. H.Liu J.Shen C. X.Zhai L.Yang G. B.Bian IEEE Trans. Instrum. Meas.2025 74 https:\/\/doi.org\/10.1109\/TIM.2024.3500060.","DOI":"10.1109\/TIM.2024.3500060"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare9010054"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-024-04292-y"},{"key":"e_1_2_8_36_1","first-page":"2578","volume-title":"Vision and Pattern Recognition","author":"Zhang P.","year":"2024"},{"key":"e_1_2_8_37_1","first-page":"1","volume":"74","author":"Liu J.","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"e_1_2_8_38_1","doi-asserted-by":"crossref","unstructured":"C.Wei S. H.Ren K. T.Guo H. H.Hu J. M.Liang Sensors2023 23 https:\/\/doi.org\/10.3390\/s23073420.","DOI":"10.3390\/s23073420"},{"key":"e_1_2_8_39_1","first-page":"106439","volume":"95","author":"Li L. M.","year":"2024","journal-title":"Process. Control"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-024-01479-z"},{"key":"e_1_2_8_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e40350"},{"key":"e_1_2_8_42_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-76577-6"},{"key":"e_1_2_8_43_1","author":"Yang Y.","year":"2025","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"e_1_2_8_44_1","doi-asserted-by":"crossref","unstructured":"Y.Niu Z.Ling J.Zhu Int. J. Intell. Syst. Volume 2024 Article ID 9987190 19 pages.https:\/\/doi.org\/10.1155\/int\/9987190.","DOI":"10.1155\/int\/9987190"},{"key":"e_1_2_8_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-023-03043-5"},{"key":"e_1_2_8_46_1","author":"Zheng S.","year":"2025","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2023.107974"},{"key":"e_1_2_8_48_1","first-page":"395","volume":"32","author":"Li W.","year":"2024","journal-title":"Journal of X-Ray Science and Technology"},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-66585-x"},{"key":"e_1_2_8_50_1","volume-title":"Computer Vision \u2013 ECCV 2024. ECCV 2024. Lecture Notes in Computer Science","author":"Ho M. Y.","year":"2025"},{"key":"e_1_2_8_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-024-01390-7"},{"key":"e_1_2_8_52_1","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12854"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13061063"},{"key":"e_1_2_8_54_1","doi-asserted-by":"publisher","DOI":"10.3390\/math11092116"},{"key":"e_1_2_8_55_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2024.111000"},{"key":"e_1_2_8_56_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12083-024-01739-2"},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-56706-x"},{"key":"e_1_2_8_58_1","doi-asserted-by":"crossref","unstructured":"O.Ronneberger P.Fischer T.Brox U\u2010net: Convolutional networks for biomedical image segmentation.In Proceedings of the 18th Inter. Conf. on Medical Image Computing and Computer\u2010Assisted Intervention Munich Germany Springer 5\u20139 October2015.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_8_59_1","unstructured":"O.Oktay J.Schlemper L.Le Folgoc M.Lee M.Heinrich K.Misawa K.Mori S.McDonagh Y. H.Nils B.Kainz B.Glocker D.Rueckert \u201cAttention u\u2010net: Learning where to look for the pancreas.\u201d arXiv preprint arXiv:1804.039992018."},{"key":"e_1_2_8_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"e_1_2_8_61_1","doi-asserted-by":"crossref","unstructured":"Y.Gao M.Zhou D. N.Metaxas \u201cUtnet: a hybrid transformer architecture for medical image segmentation\u201d inMedical Image Computing and Computer Assisted Intervention\u2013MICCAI 2021: 24th Inter. Conf. Strasbourg France September 27\u2013October 1 2021 Proceedings Part III 24. Springer2021 pp.61\u201371.","DOI":"10.1007\/978-3-030-87199-4_6"},{"key":"e_1_2_8_62_1","unstructured":"J.Chen Y.Lu Q.Yu X.Luo E.Adeli Y.Wang L.Lu A. L.Yuille Y.Zhou \u201cTransunet: Transformers make strong encoders for medical image segmentation \u201d arXiv preprint arXiv:2102.043062021."},{"key":"e_1_2_8_63_1","doi-asserted-by":"crossref","unstructured":"H.Cao Y.Wang J.Chen D.Jiang X.Zhang Q.Tian M.Wang \u201cSwin\u2010unet: Unet\u2010like pure transformer for medical image segmentation \u201d in Computer Vision\u2013ECCV 2022 Workshops: Tel Aviv Israel October 23\u201327 2022 Proc. Part III. Springer2023 pp.205\u2013218.","DOI":"10.1007\/978-3-031-25066-8_9"}],"container-title":["Advanced Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202500455","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T06:04:18Z","timestamp":1765605858000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/aisy.202500455"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":62,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["10.1002\/aisy.202500455"],"URL":"https:\/\/doi.org\/10.1002\/aisy.202500455","archive":["Portico"],"relation":{},"ISSN":["2640-4567","2640-4567"],"issn-type":[{"value":"2640-4567","type":"print"},{"value":"2640-4567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,3]]},"assertion":[{"value":"2025-04-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e202500455"}}