{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Qu X"],"funding":["National Natural Science Foundation of China","State Key Laboratory of Analytical Chemistry for Life Science"],"pagination":["1745-1751"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12667402"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(3)"],"pubmed_abstract":["Colorimetric sensors are widely utilized in biomedical detection owing to their simple operation and intuitive visual results. However, their inherent limitation in the output signal makes sensors insufficient in handling multiple biomarker combination information required for the diagnosis of highly heterogeneous diseases like breast cancer. To overcome the limitation, this study draws inspiration from the mechanism by which the human visual system perceives a myriad of colors using only three cone cell types. So, we propose a novel AI-enabled bionic mixed-color sensing technology for accurate breast cancer subtyping through exosome (EXO) analysis. This technology gives EXO a unique \"mixed color fingerprint\" by simultaneously binding color-coded nanoprobes (Ab-DyeNPs) targeting different "],"journal":["Chemical science"],"pubmed_title":["AI-enabled new sensing technology: colorimetric analysis of exosomes for precise diagnosis of breast cancer."],"pmcid":["PMC12667402"],"funding_grant_id":["5431ZZXM2508","82202294"],"pubmed_authors":["Li G","Ji C","Zhao W","Wu S","Qu X","Zeng Y","Gao C","Lu B"],"additional_accession":[]},"is_claimable":false,"name":"AI-enabled new sensing technology: colorimetric analysis of exosomes for precise diagnosis of breast cancer.","description":"Colorimetric sensors are widely utilized in biomedical detection owing to their simple operation and intuitive visual results. However, their inherent limitation in the output signal makes sensors insufficient in handling multiple biomarker combination information required for the diagnosis of highly heterogeneous diseases like breast cancer. To overcome the limitation, this study draws inspiration from the mechanism by which the human visual system perceives a myriad of colors using only three cone cell types. So, we propose a novel AI-enabled bionic mixed-color sensing technology for accurate breast cancer subtyping through exosome (EXO) analysis. This technology gives EXO a unique \"mixed color fingerprint\" by simultaneously binding color-coded nanoprobes (Ab-DyeNPs) targeting different ","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Jan","modification":"2026-06-06T19:49:02.316Z","creation":"2026-06-04T03:12:30.284Z"},"accession":"S-EPMC12667402","cross_references":{"pubmed":["41334038"],"doi":["10.1039/d5sc06650f"]}}