Similarity Computation based on Formal Concept Analysis for Colorectal Cancer Patients

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Author(s)
Xiang, J
Xu, H
Pokharel, S
Li, J
Xue, F
Zhang, P
Griffith University Author(s)
Year published
2020
Metadata
Show full item recordAbstract
Colorectal cancer is a heterogeneous disease. Its response to targeted therapies is associated with various factors, and the treatment effect differ significantly between individuals. Personalize medical treatment (PMT), which takes into consideration of individual patient characteristics, is the most effective way to deal with this issue. Patient similarity and clustering analysis is an important part in PMT. Earlier works mainly focused on similarity computation among the patients but overlook to preserve relationships. This paper presents a formal concept analysis-based approach for computing the similarity between ...
View more >Colorectal cancer is a heterogeneous disease. Its response to targeted therapies is associated with various factors, and the treatment effect differ significantly between individuals. Personalize medical treatment (PMT), which takes into consideration of individual patient characteristics, is the most effective way to deal with this issue. Patient similarity and clustering analysis is an important part in PMT. Earlier works mainly focused on similarity computation among the patients but overlook to preserve relationships. This paper presents a formal concept analysis-based approach for computing the similarity between colorectal cancer patients. The approach not only does the clustering of patients based on their similarity but also can preserve the relations between clusters in hierarchical structural form. This would allow us to build a knowledge base which is helpful for clinicians to take fast and effective decision for treatment and care of colorectal cancer patient.
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View more >Colorectal cancer is a heterogeneous disease. Its response to targeted therapies is associated with various factors, and the treatment effect differ significantly between individuals. Personalize medical treatment (PMT), which takes into consideration of individual patient characteristics, is the most effective way to deal with this issue. Patient similarity and clustering analysis is an important part in PMT. Earlier works mainly focused on similarity computation among the patients but overlook to preserve relationships. This paper presents a formal concept analysis-based approach for computing the similarity between colorectal cancer patients. The approach not only does the clustering of patients based on their similarity but also can preserve the relations between clusters in hierarchical structural form. This would allow us to build a knowledge base which is helpful for clinicians to take fast and effective decision for treatment and care of colorectal cancer patient.
View less >
Conference Title
Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
Copyright Statement
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Subject
Oncology and Carcinogenesis