Prediction models for heart failure outcomes

Harvard Dataverse2020-01-01 更新2026-04-09 收录

心力衰竭预测

临床预测模型

数据链接：

https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/FFKC2P 数据链接链接失效反馈

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资源简介：

User guides and programming codes to build and apply prediction models described in the accompanying manuscript

创建时间：

2020-01-01

RIPASA AND AIR SCORING SYSTEMS ARE SUPERIOR TO ALVARADO SCORING IN ACUTE APPENDICITIS : DATA SET

急性阑尾炎诊断评分

临床预测模型

The objective was to find the predictive accuracy of MASS and two new systems namely Appendicitis Inflammatory Response (AIR) score and Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) score, in

NIAID Data Ecosystem50

Replication Data for: External validation of an admission risk score for predicting inpatient paediatric mortality in two Kenyan public hospitals

临床预测模型

死亡率风险评估

The data was collected as part of the Clinical Information Network (CIN) project which collects routine admission data from participating hospitals. The data used for this analysis were collected betw

NIAID Data Ecosystem10

Diagnostic accuracy of CPS and external validation at various score cut-off points.

临床预测模型

准确性评估

Diagnostic accuracy of CPS and external validation at various score cut-off points.

NIAID Data Ecosystem10

Supplementary Material for: A MARKED EOSINOPHILIC INFILTRATION IN MUCOSA COULD BE A BETTER PREDICTIVE FACTOR FOR INTRACTABLE NON-ESOPHAGEAL EOSINOPHILIC GASTROINTESTINAL DISORDERS.

嗜酸性粒细胞性胃肠道疾病

临床预测模型

Introduction：Non-esophageal eosinophilic gastrointestinal disorders (non-EoE EGIDs) are rare, but their prevalence has recently increased. Although it has been reported that one-half of patients with

Figshare2023-04-21 更新40

Univariate and multivariable logistic regression analysis for association of clinical factors with presence of brain metastases at baseline.

脑转移预测

临床预测模型

Univariate and multivariable logistic regression analysis for association of clinical factors with presence of brain metastases at baseline.

Figshare2018-03-06 更新10