{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T00:13:00Z","timestamp":1778803980329,"version":"3.51.4"},"reference-count":47,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100012543","name":"Shanghai Science and Technology Development Foundation","doi-asserted-by":"publisher","award":["DZX20233100001001"],"award-info":[{"award-number":["DZX20233100001001"]}],"id":[{"id":"10.13039\/100012543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People&apos;s Republic of China","doi-asserted-by":"publisher","award":["S20240085"],"award-info":[{"award-number":["S20240085"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People&apos;s Republic of China","doi-asserted-by":"publisher","award":["STI2030-Major Projects-2022ZD0209000"],"award-info":[{"award-number":["STI2030-Major Projects-2022ZD0209000"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People&apos;s Republic of China","doi-asserted-by":"publisher","award":["STI2030-Major Projects-2022ZD0213100"],"award-info":[{"award-number":["STI2030-Major Projects-2022ZD0213100"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012600","name":"ShanghaiTech University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012600","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62131015"],"award-info":[{"award-number":["62131015"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23A20295"],"award-info":[{"award-number":["U23A20295"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82394432"],"award-info":[{"award-number":["82394432"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82441023"],"award-info":[{"award-number":["82441023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Medical Image Analysis"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.media.2026.104063","type":"journal-article","created":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T23:57:22Z","timestamp":1775260642000},"page":"104063","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A hierarchical prompt and prototype learning framework for brain disorder classification"],"prefix":"10.1016","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8298-5420","authenticated-orcid":false,"given":"Yuxiao","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaicong","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaping","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2360-4637","authenticated-orcid":false,"given":"Xin","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4458-7724","authenticated-orcid":false,"given":"Long","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weilin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoyue","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xintong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yichu","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingxia","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4692-5493","authenticated-orcid":false,"given":"Zengyang","family":"Che","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqiang","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sean","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dijia","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1522-9943","authenticated-orcid":false,"given":"Feng","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meiyun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.media.2026.104063_bib0001","doi-asserted-by":"crossref","unstructured":"Aisen, P. S., Petersen, R. C., Donohue, M., Weiner, M. W., 2015. Alzheimer\u2019s disease neuroimaging initiative 2 clinical core: progress and plans. 10.1016\/j.jalz.2015.05.005.","DOI":"10.1016\/j.jalz.2015.05.005"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0002","doi-asserted-by":"crossref","first-page":"4250","DOI":"10.1038\/s41598-021-83503-7","article-title":"Hierarchical deep learning models using transfer learning for disease detection and classification based on small number of medical images","volume":"11","author":"An","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.media.2026.104063_bib0003","doi-asserted-by":"crossref","first-page":"44","DOI":"10.3389\/fninf.2014.00044","article-title":"The insight toolkit image registration framework","volume":"8","author":"Avants","year":"2014","journal-title":"Front. Neuroinf."},{"issue":"3","key":"10.1016\/j.media.2026.104063_bib0004","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1097\/WAD.0b013e318142774e","article-title":"The national alzheimer\u2019s coordinating center (NACC) database: the uniform data set","volume":"21","author":"Beekly","year":"2007","journal-title":"Alzheimer Disease Associated. Disorders"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0005","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1148\/radiology.189.1.8372185","article-title":"Mr appearance of hemorrhage in the brain","volume":"189","author":"Bradley","year":"1993","journal-title":"Radiology"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0006","doi-asserted-by":"crossref","first-page":"4938","DOI":"10.1038\/s41467-023-40564-8","article-title":"Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke","volume":"14","author":"Brugnara","year":"2023","journal-title":"Nat. Commun."},{"key":"10.1016\/j.media.2026.104063_bib0007","unstructured":"Dosovitskiy, A., 2020. An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv: 2010.11929."},{"key":"10.1016\/j.media.2026.104063_bib0008","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"435","article-title":"Interpretable medical image classification using prototype learning and privileged information","author":"Gall\u00e9e","year":"2023"},{"key":"10.1016\/j.media.2026.104063_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2023.102303","article-title":"Multimodal transformer network for incomplete image generation and diagnosis of alzheimer\u2019s disease","volume":"110","author":"Gao","year":"2023","journal-title":"Comput. Med. Imaging Graph."},{"key":"10.1016\/j.media.2026.104063_bib0010","unstructured":"Jack, C. R., 2015. Magnetic resonance imaging in Alzheimer\u2019s disease neuroimaging initiative 2. 10.1016\/j.jalz.2015.05.002."},{"issue":"10006","key":"10.1016\/j.media.2026.104063_bib0011","doi-asserted-by":"crossref","first-page":"1835","DOI":"10.1016\/S0140-6736(15)00126-9","article-title":"Prophylactic antibiotics after acute stroke for reducing pneumonia in patients with dysphagia (STROKE-INF): a prospective, cluster-randomised, open-label, masked endpoint, controlled clinical trial","volume":"386","author":"Kalra","year":"2015","journal-title":"Lancet"},{"issue":"6","key":"10.1016\/j.media.2026.104063_bib0012","doi-asserted-by":"crossref","first-page":"318","DOI":"10.3390\/info11060318","article-title":"Hmic: hierarchical medical image classification, a deep learning approach","volume":"11","author":"Kowsari","year":"2020","journal-title":"Information"},{"key":"10.1016\/j.media.2026.104063_bib0013","unstructured":"Li, J., Sun, Q., Yan, R., Wang, Y., Fu, Y., Wei, Y., Guan, T., Shi, H., He, Y., Han, A., 2024. Diagnostic text-guided representation learning in hierarchical classification for pathological whole slide image. arXiv preprint arXiv: 2411.10709."},{"key":"10.1016\/j.media.2026.104063_bib0014","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.jneumeth.2016.03.001","article-title":"The first step for neuroimaging data analysis: DICOM to NIfTI conversion","volume":"264","author":"Li","year":"2016","journal-title":"J. Neurosci. Methods"},{"key":"10.1016\/j.media.2026.104063_bib0015","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11319","article-title":"Learning orthogonal prototypes for generalized few-shot semantic segmentation","author":"Liu","year":"2023"},{"key":"10.1016\/j.media.2026.104063_bib0016","unstructured":"Loshchilov, I., Hutter, F., 2017. Decoupled weight decay regularization. arXiv preprint arXiv: 1711.05101."},{"key":"10.1016\/j.media.2026.104063_sbref0018","series-title":"Advances in Neural Information Processing Systems","first-page":"41447","article-title":"Interpretable image classification with adaptive prototype-based vision transformers","author":"Ma","year":"2024"},{"issue":"9","key":"10.1016\/j.media.2026.104063_bib0018","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1162\/jocn.2007.19.9.1498","article-title":"Open access series of imaging studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults","volume":"19","author":"Marcus","year":"2007","journal-title":"J. Cogn. Neurosci."},{"issue":"8","key":"10.1016\/j.media.2026.104063_bib0019","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1016\/j.amjmed.2017.12.039","article-title":"Brain tumors","volume":"131","author":"McFaline-Figueroa","year":"2018","journal-title":"Am. J. Med."},{"issue":"3","key":"10.1016\/j.media.2026.104063_bib0020","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.jalz.2011.03.005","article-title":"The diagnosis of dementia due to alzheimer\u2019s disease: recommendations from the national institute on aging-alzheimer\u2019s association workgroups on diagnostic guidelines for alzheimer\u2019s disease","volume":"7","author":"McKhann","year":"2011","journal-title":"Alzheimer\u2019s Dementia"},{"key":"10.1016\/j.media.2026.104063_bib0021","series-title":"2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA)","first-page":"379","article-title":"Inconsistent node flattening for improving top-down hierarchical classification","author":"Naik","year":"2016"},{"issue":"3","key":"10.1016\/j.media.2026.104063_bib0022","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3390\/bdcc9030065","article-title":"Enhancing hierarchical classification in tree-based models using level-wise entropy adjustment","volume":"9","author":"Narushynska","year":"2025","journal-title":"Big Data Cognit. Comput."},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0023","doi-asserted-by":"crossref","first-page":"6","DOI":"10.2174\/1874196702008010006","article-title":"Human brain disorders: a review","volume":"8","author":"Naz","year":"2020","journal-title":"Open Biol. J."},{"issue":"11","key":"10.1016\/j.media.2026.104063_bib0024","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1016\/S1474-4422(06)70597-X","article-title":"Pitfalls in the diagnosis of brain tumours","volume":"5","author":"Omuro","year":"2006","journal-title":"Lancet Neurol."},{"key":"10.1016\/j.media.2026.104063_bib0025","unstructured":"Paszke, A., 2019. Pytorch: an imperative style, high-performance deep learning library. arXiv preprint arXiv: 1912.01703."},{"issue":"9361","key":"10.1016\/j.media.2026.104063_bib0026","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1016\/S0140-6736(03)12772-9","article-title":"Dementia diagnosis in developing countries: a cross-cultural validation study","volume":"361","author":"Prince","year":"2003","journal-title":"Lancet"},{"key":"10.1016\/j.media.2026.104063_bib0027","series-title":"International Conference on Machine Learning","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.media.2026.104063_bib0028","first-page":"4077","article-title":"Prototypical networks for few-shot learning","volume":"30","author":"Snell","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"3","key":"10.1016\/j.media.2026.104063_bib0029","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.jalz.2011.03.003","article-title":"Toward defining the preclinical stages of alzheimer\u2019s disease: recommendations from the national institute on aging-alzheimer\u2019s association workgroups on diagnostic guidelines for alzheimer\u2019s disease","volume":"7","author":"Sperling","year":"2011","journal-title":"Alzheimer\u2019s Dementia"},{"key":"10.1016\/j.media.2026.104063_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.130326","article-title":"Prototypeformer: learning to explore prototype relationships for few-shot image classification","volume":"640","author":"Su","year":"2025","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0031","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1038\/s44172-024-00245-w","article-title":"Achieving multi-modal brain disease diagnosis performance using only single-modal images through generative AI","volume":"3","author":"Sun","year":"2024","journal-title":"Commun. Eng."},{"issue":"Nov","key":"10.1016\/j.media.2026.104063_bib0032","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der","year":"2008","journal-title":"J. Mach. Learn. Res."},{"issue":"9","key":"10.1016\/j.media.2026.104063_bib0033","doi-asserted-by":"crossref","first-page":"1783","DOI":"10.1161\/01.STR.29.9.1783","article-title":"Diffusion-weighted magnetic resonance imaging in acute stroke","volume":"29","author":"Van Everdingen","year":"1998","journal-title":"Stroke"},{"key":"10.1016\/j.media.2026.104063_bib0034","first-page":"28187","article-title":"Transhp: image classification with hierarchical prompting","volume":"36","author":"Wang","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"8","key":"10.1016\/j.media.2026.104063_bib0035","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1016\/S1474-4422(13)70124-8","article-title":"Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration","volume":"12","author":"Wardlaw","year":"2013","journal-title":"Lancet Neurol."},{"key":"10.1016\/j.media.2026.104063_bib0036","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41591-024-03118-z","article-title":"Ai-based differential diagnosis of dementia etiologies on multimodal data","volume":"30","author":"Xue","year":"2024","journal-title":"Nat. Med."},{"key":"10.1016\/j.media.2026.104063_bib0037","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"2740","article-title":"Hd-cnn: hierarchical deep convolutional neural networks for large scale visual recognition","author":"Yan","year":"2015"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0038","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1186\/s12859-023-05529-0","article-title":"Hierarchical classification-based pan-cancer methylation analysis to classify primary cancer","volume":"24","author":"Yang","year":"2023","journal-title":"BMC Bioinf."},{"key":"10.1016\/j.media.2026.104063_bib0039","unstructured":"Ye, Y., Chen, Z., Zhang, J., Xie, Y., Xia, Y., 2024. Meduniseg: 2d and 3d medical image segmentation via a prompt-driven universal model. arXiv preprint arXiv: 2410.05905."},{"key":"10.1016\/j.media.2026.104063_bib0040","series-title":"Neuroradiology: the Requisites E-Book","author":"Yousem","year":"2010"},{"issue":"1","key":"10.1016\/j.media.2026.104063_bib0041","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1038\/s41746-024-01395-z","article-title":"Hierarchical skin lesion image classification with prototypical decision tree","volume":"8","author":"Yu","year":"2025","journal-title":"npj Digital Med."},{"key":"10.1016\/j.media.2026.104063_bib0042","unstructured":"Zhang, S., Xu, Y., Usuyama, N., Xu, H., Bagga, J., Tinn, R., Preston, S., Rao, R., Wei, M., Valluri, N., et al., 2023. BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs. arXiv preprint arXiv: 2303.00915."},{"key":"10.1016\/j.media.2026.104063_bib0043","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00234-021-02820-w","article-title":"A deep learning algorithm for white matter hyperintensity lesion detection and segmentation","volume":"64","author":"Zhang","year":"2022","journal-title":"Neuroradiology"},{"key":"10.1016\/j.media.2026.104063_bib0044","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1109\/JBHI.2024.3472011","article-title":"A modality-flexible framework for alzheimer\u2019s disease diagnosis following clinical routine","volume":"29","author":"Zhang","year":"2024","journal-title":"IEEE J. Biomed Health Inform."},{"key":"10.1016\/j.media.2026.104063_bib0045","unstructured":"Zheng, Z., Yue, X., Wang, K., You, Y., 2022. Prompt vision transformer for domain generalization. arXiv preprint arXiv: 2208.08914."},{"key":"10.1016\/j.media.2026.104063_bib0046","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"16816","article-title":"Conditional prompt learning for vision-language models","author":"Zhou","year":"2022"},{"issue":"9","key":"10.1016\/j.media.2026.104063_bib0047","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","article-title":"Learning to prompt for vision-language models","volume":"130","author":"Zhou","year":"2022","journal-title":"Int. J. Comput. Vis."}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526001313?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841526001313?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T00:02:59Z","timestamp":1778803379000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1361841526001313"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":47,"alternative-id":["S1361841526001313"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2026.104063","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A hierarchical prompt and prototype learning framework for brain disorder classification","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2026.104063","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104063"}}