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Ensemble Learning for Predicting Gynecological Oncology Patients Using Travel Distance

机译：用于预测使用旅行距离预测妇科肿瘤患者的合奏学习

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作者
Jarett, Jamie.;
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作者单位

State University of New York at Binghamton.;

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授予单位 State University of New York at Binghamton.;
学科
学位 M.S.
年度 2019
页码 62 p.
总页数 62
原文格式 PDF
正文语种 eng
中图分类 AAI22616435;
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机译：Celecoxib的分层随机双盲期II试验治疗宫颈上皮内瘤形成的患者：VEGF血清水平的潜在预测值：NRG肿瘤学/妇科肿瘤学群体研究
2. Validation of the Predictive Value of Modeled Human Chorionic Gonadotrophin Residual Production in Low-Risk Gestational Trophoblastic Neoplasia Patients Treated in NRG Oncology/Gynecologic Oncology Group-174 Phase III Trial [J] . International journal of gynecological cancer: official journal of the International Gynecological Cancer Society . 2016,第1期

机译：在NRG肿瘤/妇科肿瘤组174组III期治疗的低风险妊娠滋养细胞肿瘤患者中模拟人绒毛膜促性腺激素残留产生的预测价值的验证
3. Nomograms Predicting Progression-Free Survival, Overall Survival, and Pelvic Recurrence in Locally Advanced Cervical Cancer Developed From an Analysis of Identifiable Prognostic Factors in Patients From NRG Oncology/Gynecologic Oncology Group Randomized Trials of Chemoradiotherapy [J] . Rose Peter G., Java James, Whitney Charles W., Journal of Clinical Oncology . 2015,第19期

机译：通过对NRG肿瘤/妇科肿瘤组化学放疗的随机预后因素进行分析，可预测局部晚期宫颈癌的无进展生存期，总生存期和盆腔复发的线型图
4. An ensemble of machine learning and anti-learning methods for predicting tumour patient survival rates [C] . Roadknight Christopher, Suryanarayanan Durga, Aickelin Uwe, IEEE International Conference on Data Science and Advanced Analytics . 2015

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5. Utilizing Data Mining Techniques and Ensemble Learning to Predict Development of Surgical Site Infections in Gynecologic Cancer Patients [D] . McDonough, John R. 2018

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6. Nomograms Predicting Progression-Free Survival Overall Survival and Pelvic Recurrence in Locally Advanced Cervical Cancer Developed From an Analysis of Identifiable Prognostic Factors in Patients From NRG Oncology/Gynecologic Oncology Group Randomized Trials of Chemoradiotherapy [O] . Peter G. Rose, James Java, Charles W. Whitney, -1

机译：通过对NRG肿瘤/妇科肿瘤组化学放疗的随机预后因素进行分析可预测局部晚期宫颈癌的无进展生存期总生存期和盆腔复发的线型图
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机译：通过对NRG肿瘤/妇科肿瘤组化学放疗的随机预后因素进行分析，可预测局部晚期宫颈癌的无进展生存期，总生存期和盆腔复发的线型图

Ensemble Learning for Predicting Gynecological Oncology Patients Using Travel Distance

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