Co-Occurrence Analysis for Discovery of Novel Breast Cancer Pathology Patterns

To discover novel patterns in pathology co-occurrence, we have developed algorithms to analyze and visualize pathology co-occurrence. With access to a database of pathology reports, collected under a single protocol and reviewed by a single pathologist, we can conduct an analysis greater in its scop...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2006-07, Vol.10 (3), p.497-503
Hauptverfasser:	Maskery, S.M., Yonghong Zhang, Jordan, R.M., Hai Hu, Hooke, J.A., Shriver, C.D., Liebman, M.N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Access protocols Algorithm design and analysis Algorithms Artificial Intelligence Bioinformatics Biomedical informatics Biopsy - methods Breast Breast cancer Breast Neoplasms - classification Breast Neoplasms - pathology Cluster Analysis co-occurrence analysis Data visualization Density Female Genomics Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Information Storage and Retrieval - methods Information systems Pathology Pattern analysis Pattern Recognition, Automated - methods Proteomics Reproducibility of Results Retrospective Studies Sensitivity and Specificity User-Computer Interface Visual databases
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