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CrossRef Text and Data Mining |
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Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer |
Mohamed Hosny Osman, Reham Hosny Mohamed, Hossam Mohamed Sarhan, Eun Jung Park, Seung Hyuk Baik, Kang Young Lee, Jeonghyun Kang |
Cancer Research and Treatment. 2022;54(2):517-524. Published online 2021 June 15 DOI: https://doi.org/10.4143/crt.2021.206 |
Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer Construction of a Prognostic Model for Predicting Overall Survival of Patients with Colorectal Cancer A multi-omics machine learning framework in predicting the survival of colorectal cancer patients Machine Learning With K-Means Dimensional Reduction for Predicting Survival Outcomes in Patients With Breast Cancer Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system MON-PP001: C-Reactive Protein to Albumin Ratio is Useful for Predicting Postoperative Survival of Patients Undergoing Colorectal Cancer Surgery Prognostic Prediction Models for Postoperative Patients with Stage I to III Colorectal Cancer: A Retrospective Study Based on Machine Learning Methods Prognostic Prediction Models for Postoperative Patients with Stage I to III Colorectal Cancer: A Retrospective Study Based on Machine Learning Methods Predicting survival in patients with colorectal cancer Prognostic Nomograms based on Homogeneous and Heterogeneous Associated Factors for Predicting the Overall Survival of Colorectal Cancer Patients with Distant Metastases |
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