基于机器学习算法预测早期结直肠腺癌病人内镜治疗后的癌症特异性生存状态OA北大核心CSTPCD
Prediction of cancer-specific survival status of patients with early colorectal adenocarcinoma after endoscopic therapy based on machine learning algorithms
目的:基于机器学习算法构建早期结直肠腺癌病人经内镜治疗后的癌症特异性生存状态预测模型.方法:基于流行病学和最终结果数据库获取1 786例经内镜治疗后的早期结直肠腺癌病人资料,提取病人年龄、性别、种族、癌症原发部位、癌细胞分化程度、癌症组织病理学类型、放疗情况、化疗情况、肿瘤大小、病理情况、婚姻状况信息.经单因素Logistic回归与多因素Logistic回归分析确定早期结直肠腺癌病人内镜治疗后生存预后的独立影响因素.以8∶2的比例将病人分为训练集…查看全部>>
Objective:To construct a cancer-specific survival status prediction model for patients with early colorectal adenocarcinoma after endoscopic treatment used machine learning algorithms.Methods:Based on SEER database,the data of 1 786 patients with early colorectal adenocarcinoma after endoscopic treatment were obtained,and the information included age,sex,race,cancer primary site,degree of cancer cell differentiation,pathological type of cancer tissue,radioth…查看全部>>
李志宏;蔡迎彬;王岩;樊华;伊丽米奴尔∙阿合买;李紫梅
新疆医科大学护理学院,新疆 830011新疆医科大学附属肿瘤医院新疆医科大学附属肿瘤医院新疆医科大学附属肿瘤医院新疆医科大学第三临床医学院新疆医科大学第三临床医学院
机器学习早期结直肠癌腺癌内镜治疗生存状态预测模型影响因素护理
machine learningearly colorectal canceradenocarcinomaendoscopic therapysurvival statepredictive modelsinfluencing factornursing
《护理研究》 2024 (14)
2459-2467,9
新疆维吾尔自治区自然科学基金资助项目,编号:2022D01C299
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