Article ; Online: A machine learning approach toward automating spatial identification of LAG3+/CD3+ cells in ulcerative colitis.
2023 Volume 13, Issue 1, Page(s) 21759
Abstract: Over the past decade, automation of digital image analysis has become commonplace in both research and clinical settings. Spurred by recent advances in artificial intelligence and machine learning (AI/ML), tissue sub-compartments and cellular phenotypes ... ...
Abstract | Over the past decade, automation of digital image analysis has become commonplace in both research and clinical settings. Spurred by recent advances in artificial intelligence and machine learning (AI/ML), tissue sub-compartments and cellular phenotypes within those compartments can be identified with higher throughput and accuracy than ever before. Recently, immune checkpoints have emerged as potential targets for auto-immune diseases. As such, spatial identification of these proteins along with immune cell markers (e.g., CD3 |
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MeSH term(s) | Humans ; Artificial Intelligence ; Colitis, Ulcerative ; Algorithms ; Fluorescent Antibody Technique ; Machine Learning ; Biomarkers |
Chemical Substances | Biomarkers |
Language | English |
Publishing date | 2023-12-08 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2615211-3 |
ISSN | 2045-2322 ; 2045-2322 |
ISSN (online) | 2045-2322 |
ISSN | 2045-2322 |
DOI | 10.1038/s41598-023-49163-5 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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