{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T01:07:11Z","timestamp":1763514431255,"version":"3.45.0"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T00:00:00Z","timestamp":1763424000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T00:00:00Z","timestamp":1763424000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62406347","62202302"],"award-info":[{"award-number":["62406347","62202302"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-025-02042-x","type":"journal-article","created":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:36:07Z","timestamp":1763469367000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Large language models driven neural architecture search for universal and lightweight disease diagnosis on histopathology slide images"],"prefix":"10.1038","volume":"8","author":[{"given":"Xiu","family":"Su","sequence":"first","affiliation":[]},{"given":"Qinghua","family":"Mao","sequence":"additional","affiliation":[]},{"given":"Zhongze","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Xi","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Shan","family":"You","sequence":"additional","affiliation":[]},{"given":"Yue","family":"Liao","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,18]]},"reference":[{"key":"2042_CR1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-90064-6","volume":"15","author":"SE Mousavi","year":"2025","unstructured":"Mousavi, S. E., Ilaghi, M., Elahi Vahed, I. & Nejadghaderi, S. A. Epidemiology and socioeconomic correlates of gastric cancer in Asia: results from the GLOBOCAN 2020 data and projections from 2020 to 2040. Sci. Rep. 15, 6529 (2025).","journal-title":"Sci. Rep."},{"key":"2042_CR2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-48666-7","volume":"15","author":"A Claudio Quiros","year":"2024","unstructured":"Claudio Quiros, A. et al. Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides. Nat. Commun. 15, 4596 (2024).","journal-title":"Nat. Commun."},{"key":"2042_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-43172-8","volume":"14","author":"S Wang","year":"2023","unstructured":"Wang, S. et al. Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images. Nat. Commun. 14, 7872 (2023).","journal-title":"Nat. Commun."},{"key":"2042_CR4","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-44824-z","volume":"15","author":"J Ma","year":"2024","unstructured":"Ma, J. et al. Segment anything in medical images. Nat. Commun. 15, 654 (2024).","journal-title":"Nat. Commun."},{"key":"2042_CR5","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-44560-w","volume":"15","author":"X Fu","year":"2024","unstructured":"Fu, X. et al. BIDCELL: biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data. Nat. Commun. 15, 509 (2024).","journal-title":"Nat. Commun."},{"key":"2042_CR6","unstructured":"Achiam, J. et al. Gpt-4 technical report. Preprint at https:\/\/arxiv.org\/abs\/2303.08774 (2023)."},{"key":"2042_CR7","unstructured":"Li, J., Li, D., Savarese, S. & Hoi, S. BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models. In International conference on machine learning, 19730\u201319742 (PMLR, 2023)."},{"key":"2042_CR8","unstructured":"Kirillov, A. et al. Segment anything. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, 4015\u20134026 (IEEE, 2023)."},{"key":"2042_CR9","doi-asserted-by":"publisher","first-page":"2307","DOI":"10.1038\/s41591-023-02504-3","volume":"29","author":"Z Huang","year":"2023","unstructured":"Huang, Z., Bianchi, F., Yuksekgonul, M., Montine, T. J. & Zou, J. A visual\u2013language foundation model for pathology image analysis using medical Twitter. Nat. Med. 29, 2307\u20132316 (2023).","journal-title":"Nat. Med."},{"key":"2042_CR10","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1038\/s41591-024-02856-4","volume":"30","author":"MY Lu","year":"2024","unstructured":"Lu, M. Y. et al. A visual-language foundation model for computational pathology. Nat. Med. 30, 863\u2013874 (2024).","journal-title":"Nat. Med."},{"key":"2042_CR11","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1109\/MWC.005.2300481","volume":"31","author":"Z Chen","year":"2024","unstructured":"Chen, Z., Yang, H. H., Tay, Y., Chong, K. F. E. & Quek, T. Q. The role of federated learning in a wireless world with foundation models. IEEE Wirel. Commun. 31, 42\u201349 (2024).","journal-title":"IEEE Wirel. Commun."},{"key":"2042_CR12","unstructured":"Hu, E. J. et al. LoRA: Low-rank adaptation of large language models. International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=nZeVKeeFYf9 (2022)."},{"key":"2042_CR13","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S. & Sun, J. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770\u2013778 (IEEE, 2016).","DOI":"10.1109\/CVPR.2016.90"},{"key":"2042_CR14","unstructured":"Tan, M. & Le, Q. Efficientnet: rethinking model scaling for convolutional neural networks. In International Conference on Machine Learning, 6105\u20136114 (PMLR, 2019)."},{"key":"2042_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Z. et al. Swin transformer: hierarchical vision transformer using shifted windows. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, 10012\u201310022 (2021).","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"2042_CR16","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P. & Brox, T. U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-assisted Intervention\u2013MICCAI 2015: 18th International Conference, 234\u2013241 (Springer, 2015).","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2042_CR17","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y. et al. Feature pyramid networks for object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2117\u20132125 (IEEE, 2017).","DOI":"10.1109\/CVPR.2017.106"},{"key":"2042_CR18","doi-asserted-by":"crossref","unstructured":"Ci, Y. et al. Evolving search space for neural architecture search. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, 6659\u20136669 (IEEE, 2021).","DOI":"10.1109\/ICCV48922.2021.00659"},{"key":"2042_CR19","doi-asserted-by":"crossref","unstructured":"Guo, Z. et al. Single path one-shot neural architecture search with uniform sampling. In Computer Vision\u2013ECCV 2020: 16th European Conference, 544\u2013560 (Springer, 2020).","DOI":"10.1007\/978-3-030-58517-4_32"},{"key":"2042_CR20","doi-asserted-by":"crossref","unstructured":"Chen, M., Peng, H., Fu, J. & Ling, H. Autoformer: Searching transformers for visual recognition. In Proceedings of the IEEE\/CVF international conference on computer vision, 12270\u201312280 (IEEE, 2021).","DOI":"10.1109\/ICCV48922.2021.01205"},{"key":"2042_CR21","first-page":"17955","volume":"33","author":"H Peng","year":"2020","unstructured":"Peng, H. et al. Cream of the crop: distilling prioritized paths for one-shot neural architecture search. Adv. Neural Inf. Process. Syst. 33, 17955\u201317964 (2020).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"2042_CR22","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A. & Chen, L.-C. Mobilenetv2: Inverted residuals and linear bottlenecks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 4510\u20134520 (IEEE, 2018).","DOI":"10.1109\/CVPR.2018.00474"},{"key":"2042_CR23","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L. & Sun, G. Squeeze-and-excitation networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 7132\u20137141 (IEEE, 2018).","DOI":"10.1109\/CVPR.2018.00745"},{"key":"2042_CR24","first-page":"27730","volume":"35","author":"L Ouyang","year":"2022","unstructured":"Ouyang, L. et al. Training language models to follow instructions with human feedback. Adv. Neural Inf. Process. Syst. 35, 27730\u201327744 (2022).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"2042_CR25","unstructured":"Rafailov, R. et al. Direct preference optimization: Your language model is secretly a reward model. In Advances in Neural Information Processing Systems, 36 (NIPS, 2024)."},{"key":"2042_CR26","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-025-04489-9","volume":"12","author":"S Lou","year":"2025","unstructured":"Lou, S. et al. A large histological images dataset of gastric cancer with tumour microenvironment annotation for ai. Sci. Data 12, 138 (2025).","journal-title":"Sci. Data"},{"key":"2042_CR27","doi-asserted-by":"crossref","unstructured":"Pham, T. C. et al. Improving binary skin cancer classification based on best model selection method combined with optimizing full connected layers of Deep CNN. In 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR), 1\u20136 (IEEE, 2020).","DOI":"10.1109\/MAPR49794.2020.9237778"},{"key":"2042_CR28","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-01981-y","volume":"10","author":"S Ali","year":"2023","unstructured":"Ali, S. et al. A multi-centre polyp detection and segmentation dataset for generalisability assessment. Sci. Data 10, 19 (2023).","journal-title":"Sci. Data"},{"key":"2042_CR29","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1109\/TBME.2015.2496264","volume":"63","author":"FA Spanhol","year":"2016","unstructured":"Spanhol, F. A., Oliveira, L. S., Petitjean, C. & Heutte, L. A dataset for breast cancer histopathological image classification. IEEE Trans. Biomed. Eng. 63, 1455\u20131462 (2016).","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"2042_CR30","unstructured":"Wang, Z. & Yang, J. Diabetic retinopathy detection via deep convolutional networks for discriminative localization and visual explanation. In AAAI Workshops, 514\u2013521 (AAAI, 2018)."},{"key":"2042_CR31","unstructured":"Wang, H., Ahn, E. & Kim, J. A dual-branch self-supervised representation learning framework for tumour segmentation in whole slide images. Preprint at https:\/\/arxiv.org\/abs\/2303.11019 (2023)."},{"key":"2042_CR32","unstructured":"Gamper, J. et al. Pannuke dataset extension, insights and baselines. Preprint at https:\/\/arxiv.org\/abs\/2003.10778 (2020)."},{"key":"2042_CR33","doi-asserted-by":"publisher","first-page":"101563","DOI":"10.1016\/j.media.2019.101563","volume":"58","author":"S Graham","year":"2019","unstructured":"Graham, S. et al. Hover-Net: simultaneous segmentation and classification of nuclei in multi-tissue histology images. Med. Image Anal. 58, 101563 (2019).","journal-title":"Med. Image Anal."},{"key":"2042_CR34","doi-asserted-by":"crossref","unstructured":"P\u00e9rez-Cano, J. et al. Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue. Heliyon 10, e28463 (2024).","DOI":"10.1016\/j.heliyon.2024.e28463"},{"key":"2042_CR35","unstructured":"Li, L. & Talwalkar, A. Random search and reproducibility for neural architecture search. In Uncertainty in Artificial Intelligence, 367\u2013377 (PMLR, 2020)."},{"key":"2042_CR36","unstructured":"Bender, G., Kindermans, P.-J., Zoph, B., Vasudevan, V. & Le, Q. Understanding and simplifying one-shot architecture search. In International Conference on Machine Learning, 550\u2013559 (PMLR, 2018)."},{"key":"2042_CR37","unstructured":"Pham, H., Guan, M., Zoph, B., Le, Q. & Dean, J. Efficient neural architecture search via parameters sharing. In International Conference on Machine Learning, 4095\u20134104 (PMLR, 2018)."},{"key":"2042_CR38","doi-asserted-by":"crossref","unstructured":"Tan, M. et al. MnasNet: platform-aware neural architecture search for mobile. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2820\u20132828 (IEEE, 2019).","DOI":"10.1109\/CVPR.2019.00293"},{"key":"2042_CR39","doi-asserted-by":"crossref","unstructured":"Real, E., Aggarwal, A., Huang, Y. & Le, Q. V. Regularized evolution for image classifier architecture search. In Proceedings of the AAAI Conference on Artificial Intelligence, 33, 4780\u20134789 (AAAI, 2019).","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"2042_CR40","unstructured":"Zheng, M. et al. Can gpt-4 perform neural architecture search? Preprint at https:\/\/arxiv.org\/abs\/2304.10970 (2023)."},{"key":"2042_CR41","unstructured":"Dosovitskiy, A. et al. An image is worth 16x16 words: transformers for image recognition at scale. International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=YicbFdNTTy (2021)."},{"key":"2042_CR42","doi-asserted-by":"crossref","unstructured":"Su, X. et al. ViTAS: vision transformer architecture search. In European Conference on Computer Vision, 139\u2013157 (Springer, 2022).","DOI":"10.1007\/978-3-031-19803-8_9"},{"key":"2042_CR43","unstructured":"Simonyan, K. & Zisserman, A. Very deep convolutional networks for large-scale image recognition. In 3rd International Conference on Learning Representations (eds, Bengio, Y. & LeCun, Y.) (ICLR, 2015)."},{"key":"2042_CR44","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1038\/s41592-023-02151-z","volume":"21","author":"L Maier-Hein","year":"2024","unstructured":"Maier-Hein, L. et al. Metrics reloaded: recommendations for image analysis validation. Nat. Methods 21, 195\u2013212 (2024).","journal-title":"Nat. Methods"},{"key":"2042_CR45","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T. et al. Language models are few-shot learners. Adv. Neural Inf. Process. Syst. 33, 1877\u20131901 (2020).","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02042-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T01:04:04Z","timestamp":1763514244000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02042-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,18]]},"references-count":45,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["2042"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-02042-x","relation":{},"ISSN":["2398-6352"],"issn-type":[{"type":"electronic","value":"2398-6352"}],"subject":[],"published":{"date-parts":[[2025,11,18]]},"assertion":[{"value":"2 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"682"}}