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題名:建構多階段混合式分類架構於肝癌患者復發預測之研究
書刊名:數據分析
作者:李岳樺沈湘莉呂奇傑周茂振
作者(外文):Lee, Yueh-huaShen, Hsiang-liLu, Chi-jieJhou, Mao-jhen
出版日期:2021
卷期:16:2
頁次:頁43-57
主題關鍵詞:肝癌復發特徵選取資料不平衡混合預測模式Liver cancer recurrenceFeature selectionData imbalanceHybrid prediction model
原始連結:連回原系統網址new window
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  • 點閱點閱:7
期刊論文
1.Friedman, Jerome H.(1991)。Multivariate Adaptive Regression Splines。The Annals of Statistics,19(1),1-67。  new window
2.Gu, X.、Ni, T.、Wang, H.(2014)。New fuzzy support vector machine for the class imbalance problem in medical datasets classification。The Scientific World Journal,2014(9)。  new window
3.Fu, G. S.、Levin-Schwartz, Y.、Lin, Q. H.、Zhang, D.(2019)。Machine Learning for Medical Imaging。Journal of Healthcare Engineering,2019。  new window
4.Rahman, S.、Walker, R.、Lloyd, M.、Grace, B.、van Boxel, G.、Kingma, F.(2019)。Machine learning to predict early recurrence after oesophageal cancer surgery。Eur. J. Surg. Oncol.,45(11)。  new window
5.Leon, J.、Namuche, F.、Montenegro, P. C.、Flores, C. J.(2019)。Risk factors predicting colorectal cancer recurrence in a Latin American population。J. Clin. Oncol.,37(15)。  new window
6.Kourou, K.、Exarchos, T. P.、Exarchos, K. P.、Karamouzis, M. V.、Fotiadis, D. I.(2015)。Machine learning applications in cancer prognosis and prediction。Computational and Structural Biotechnology Journal,13,8-17。  new window
7.Sun, T.、Wang, J.、Li, X.、Lv, P.、Liu, F.、Luo, Y.(2013)。Comparative evaluation of support vector machines for computer aided diagnosis of lung cancer in CT based on a multi-dimensional data set。Computer Methods and Programs in Biomedicine,111(2),519-524。  new window
8.Wong, N. C.、Lam, C.、Patterson, L.、Shayegan, B.(2019)。Use of machine learning to predict early biochemical recurrence after robot-assisted prostatectomy。BJU Int.,123(1),51-57。  new window
9.Yu, Z.、Lu, H.、Si, H.、Liu, S.、Li, X.、Gao, C.(2015)。A highly efficient gene expression programming (GEP) model for auxiliary diagnosis of small cell lung cancer。PLOS ONE,10(5)。  new window
10.Santos, M. S.、Abreu, P. H.、García-Laencina, P. J.、Simão, A.、Carvalho, A.(2015)。A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients。Journal of Biomedical Informatics,58,49-59。  new window
11.Cortes, Corinna、Vapnik, Vladimir N.(1995)。Support-Vector Networks。Machine Learning,20(3),273-297。  new window
會議論文
1.Chen, T. C.、Guestrin, C.(2016)。Xgboost: A scalable tree boosting system。The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,(會議日期: 13-17 August, 2016)。ACM。785-794。  new window
學位論文
1.李佳怡(2008)。利用決策樹、邏輯斯迴歸及類神經網路複合模型分析公開微陣列資料集乳癌復發基因及其效能之探討(碩士論文)。國防醫學院。  延伸查詢new window
2.朱慧祺(2008)。資料探勘乳部腫瘤存活分析模式之建構(碩士論文)。輔仁大學。  延伸查詢new window
3.方彥均(2018)。以機器學習建立一流感重症患者死亡預測模型(碩士論文)。國立中興大學。  延伸查詢new window
4.田昀靈(2018)。應用機器學習法對無顯影電腦斷層肝影像進行分類之研究(碩士論文)。義守大學。  延伸查詢new window
5.林佩樺(2015)。整合機器學習與重複採樣技術於卵巢癌分期預測模型之建立(碩士論文)。國立臺中科技大學。  延伸查詢new window
6.林曜璋(2012)。彩色濾光片瑕疵特徵選取與分類之研究(碩士論文)。義守大學。  延伸查詢new window
7.張智瑝(2012)。應用資料探勘探討口腔癌復發預測模型之研究(碩士論文)。國立雲林科技大學。  延伸查詢new window
8.梁嘉德(2018)。肝癌病患經治療後腫瘤復發分析與預測模式的建立(博士論文)。國立臺灣大學。  延伸查詢new window
9.陳家欣(2018)。利用機器學習預測慢性腎臟病分期及挖掘危險因子(碩士論文)。國立交通大學。  延伸查詢new window
10.盧贊(2018)。應用機器學習分析及篩選卵巢癌標記基因於微陣列晶片暨基因網路建構(碩士論文)。國立中興大學。  延伸查詢new window
11.劉子毅(2018)。運用資料探勘技術建構大腸進行性腺瘤之預測模型(碩士論文)。國立中正大學。  延伸查詢new window
12.盧月霞(2010)。運用倒傳遞類神經網路、多元適應性雲形迴歸模型及自我相關整合移動平均建構個股股價預測模式--以台積電、日月光為例(碩士論文)。輔仁大學。  延伸查詢new window
圖書
1.Vapnik, V.(1995)。The nature of statistical learning theory。New York:Springer。  new window
2.Vapnik, Vladimir N.(1998)。Statistical Learning Theory。John Wiley and Sons, Inc.。  new window
 
 
 
 
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