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COLLABORATIVE CLUSTERING OF SUBJECTS AND RADIOMIC FEATURES FOR PREDICTING CLINICAL OUTCOMES OF RECTAL CANCER PATIENTS
Most machine learning approaches in radiomics studies ignore the underlying difference of radiomic features computed from heterogeneous groups of patients, and intrinsic correlations of the features are not fully exploited yet. In order to better predict clinical outcomes of cancer patients, we adop...
में बचाया:
| में प्रकाशित: | Proc IEEE Int Symp Biomed Imaging |
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| मुख्य लेखकों: | , , , , , , , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
2019
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6892162/ https://ncbi.nlm.nih.gov/pubmed/31803347 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI.2019.8759512 |
| टैग : |
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