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Most predictive features when predicting death within five years.

NIAID Data Ecosystem2026-05-01 收录

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https://figshare.com/articles/dataset/Most_predictive_features_when_predicting_death_within_five_years_/24028967 数据链接链接失效反馈

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Most predictive features when predicting death within five years.

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创建时间：

2023-08-24

药物疗效

生存分析

Aims and objective: To estimate the effect of losartan 50 mg on survival of post-dialysis euvolemic hypertensive patients. Methodology: A single center, prospective, single

DataCite Commons2020-08-26 更新60

Mortality hazard association with ABSI from HALS1 and HALS2.

死亡风险预测

身体形状指数与死亡率关联

Results of Cox proportional hazard modeling for mortality risk with ABSI1 or ABSI2 (ABSI from HALS1 or HALS2 measurements, respectively) or ΔABSI (ABSI2 minus ABSI1), or combinations thereof, taken as

NIAID Data Ecosystem20

Survival analyses for breast cancer mortality by reported exercise level.

乳腺癌预后

生存分析

*Adjusted for follow-up age (age, age2), race, menopause, and oral contraceptive and estrogen or estrogen/progesterone use. Additional adjustment for BMI as indicated.

Figshare2015-12-02 更新00

Predictive Analyses Of Validation Cohort (n = 439).

临床预测模型

生存分析

a: Univariate analysis (Log-rank method); P<0.05 was considered statistically significant. b: Multivariate analysis (Cox proportional hazard model), P<0.05 was considered statistically significant. Ab

NIAID Data Ecosystem20

Red wolf fates by our classifications, 1987–2018 for 508 radio-collared adults.

濒危物种监测

生存分析

The variable n (known fate subset) estimates the sum of known COD, and m (unknown subset) estimates the sum of FU and unknown COD. FU are those wolves who were radio-collared but were lost to USFWS mo

NIAID Data Ecosystem10

Most predictive features when predicting death within five years.

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