fct> 1 50to70 Female STAGE I DECEASED...50to70 Female STAGE I LIVING 16 3 50to70 Female STAGE II DECEASED...50to70 Female STAGE II LIVING 11 5 50to70 Female STAGE III DECEASED...11 1 AGE 50to70 2 LIVING 16 2 AGE 50to70 3 DECEASED 3...3 AGE 50to70 4 LIVING 11 4 AGE 50to70 5 DECEASED 8 5
setName(final String value) { this.name = value; } /** * Getter for property "deceased...; } /** * Setter for property deceased...* @param value */ public void setDeceased(final boolean value) { deceased = value..." [deceased]" : " [alive]"); } } Use in a JavaServer Page testPersonBean.jsp; deceased"/> <form name="beanTest"
事件时间分布如下：死亡（DECEASED）和存活（LIVING） dat=choose_clinicaldata[choose_clinicaldata$OS_MONTHS > 0,] table(dat...$OS_STATUS) ## ## DECEASED LIVING ## 154 930 attach(dat) ## The following object is masked...object is masked from package:base: ## ## T ## 估计KM生存曲线 my.surv DECEASED...Stage IV 15 5 ## Stage X 7 5 my.surv DECEASED...'),25)) library(survival) my.surv DECEASED') ## The status indicator,
TCGA-CS-4938 LIVING 3574 NA #> 2: TCGA-CS-4941 DECEASED...NA 234 #> 3: TCGA-CS-4942 DECEASED NA...1335 #> 4: TCGA-CS-4943 DECEASED 481 1106 meta = clinical exprSet
OS_STATUS','SEX')] > head(phe) OS_MONTHS OS_STATUS SEX TCGA.AB.2882.03 11.99 1:DECEASED...Female TCGA.AB.2991.03 59.99 0:LIVING Female TCGA.AB.2847.03 19.97 1:DECEASED Male TCGA.AB....2979.03 22.04 0:LIVING Female TCGA.AB.2818.03 9.95 1:DECEASED Female TCGA.AB.2927.03...2.96 1:DECEASED Female 有了 OS_MONTHS OS_STATUS SEX，做一个简单的生存分析就太简单了。
., data = train_covid)) heat_tree(x = x, label_map = c(`1` = 'Deceased', `0` = 'Survived')) plot of
########### table=matrix(c(55,62,75,181),nrow=2) colnames(table)=c("High","Low") rownames(table)=c("Deceased
['Sex'].apply(lambda s: 1 if s == 'male' else 0) # 缺失字段填充为0 data = data.fillna(0) # 增加一列'身亡' data['Deceased...', 'Age', 'Pclass', 'SibSp', 'Parch', 'Fare']] dataset_X = dataset_X.as_matrix() dataset_Y = data[['Deceased
执行 Deceased::status()，你期望得到什么，肯定是 Decased 类的 getStatus() 返回的值对么？可是结果返回了 Person::status() 的值。
he wants to go to Oldtown to train at the Citadel to become a maester, so he can return and take the deceased
st.markdown("The following table gives you a real-time analysis of the confirmed, active, recovered and deceased
Overall_Survival_month.txt",header=T,sep="\t") #将样本ID号作为行名 rownames(os)=os$Patient.ID #删掉生存状态中:及后面的内容 #eg. 1:DECEASED
写一个UPDATE，将任何死亡动物重命名为"DECEASED"。如果你尝试说他们是"DEAD"，它会失败，因为 SQL 会认为你的意思是，将其设置为名为"DEAD"的列，这不是你想要的。
patients with either LUAD (n = 13), LUSC (n = 8) or undetermined lung cancer (LC, n = 4), and two healthy deceased
=True) plt.legend(['Survived', 'Died']) plt.title('Density Plot of Age for Surviving Population and Deceased...True) plt.legend(['Survived', 'Died']) plt.title('Density Plot of Fare for Surviving Population and Deceased
www.kaggle.com/c/titanic 题目描述： 输入：乘客信息，包括姓名、性别、客舱等级、年龄等 输出：判别每个乘客是否幸存 题目分析： 二分类问题：Survived (=1) or Deceased
, keytype="TXNAME") 参考结果 16：对有临床信息的表达矩阵批量做生存分析 题目 使用R实现生存分析： 用my.surv DECEASED...1:ncol(dat)) os_years=abs(floor(rnorm(ncol(dat),mean = 50,sd=20))) os_status=sample(rep(c('LIVING','DECEASED...'),25)) library(survival) my.surv DECEASED') ## The status indicator,...TRUE/FALSE (TRUE = death) or 1/2 (2=death). ## And most of the time we just care about the time od DECEASED
该新闻附设两条文章摘要，Store highlights * Navy identifies deceased sailor as Jason Kortz, who leaves behind a wife...Statement says he was "epitome of a quiet professional" 论文提议把这两条文章摘要转换为提问 q 和答案 a，譬如， 提问 q: Navy identifies deceased
"patient") tmp=na.omit(tmp) colnames(tmp)[4]="OS.time" colnames(tmp)[5]="OS" tmp$OS=ifelse(tmp$OS=="DECEASED
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