Identifying heterogeneous subgroups of systemic autoimmune diseases by applying a joint dimension reduction and clustering approach to immunomarkers Article Swipe

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Chia-Wei Chang , Hsin‐Yao Wang , Wan-Ying Lin , Yu-Chiang Wang , Wei-Lin Lo , Ting‐Wei Lin , Jia-Ruei Yu , Yi‐Ju Tseng ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.1186/s13040-024-00389-7

The immunomarker-driven clustering method could recognise more clinically relevant subgroups of the SADs and would provide a more precise diagnosis basis.

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Cluster analysis Dimension (graph theory) Medicine Computer science Data mining Artificial intelligence Mathematics Pure mathematics

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Type: article
Language: en
Landing Page: http://doi.org/10.1186/s13040-024-00389-7
OA Status: gold
References: 43
Related Works: 10
OpenAlex ID: https://openalex.org/W4402581354

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OpenAlex ID: https://openalex.org/W4402581354

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DOI: https://doi.org/10.1186/s13040-024-00389-7

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Title: Identifying heterogeneous subgroups of systemic autoimmune diseases by applying a joint dimension reduction and clustering approach to immunomarkers

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-09-16

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Authors: Chia-Wei Chang, Hsin‐Yao Wang, Wan-Ying Lin, Yu-Chiang Wang, Wei-Lin Lo, Ting‐Wei Lin, Jia-Ruei Yu, Yi‐Ju Tseng

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Landing page: https://doi.org/10.1186/s13040-024-00389-7

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OA URL: https://doi.org/10.1186/s13040-024-00389-7

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Concepts: Cluster analysis, Dimension (graph theory), Medicine, Computer science, Data mining, Artificial intelligence, Mathematics, Pure mathematics

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