Predicting Stroke Risk Dataset

Figshare2025-04-06 更新2026-04-28 收录

中风风险预测

临床预测模型

数据链接：

https://figshare.com/articles/dataset/_b_Predicting_Stroke_Risk_Dataset_b_/28737218 数据链接链接失效反馈

官方服务：

资源简介：

This study addresses stroke as a critical global health issue by employing a comprehensive, data-driven approach to improve early risk prediction and intervention.

创建时间：

2025-04-06

Predictive values of PcvO2 to detect Co-oximetry_ScvO2 value ≥ 70% in different populations.

重症监护氧合监测

临床预测模型

The best cutoff PcvO2 value was ≥36 mmHg for the whole and non-septic shock patients, and ≥ 35 mmHg for septic shock patients.

Figshare2018-11-08 更新50

Performance of ML algorithms in MIMIC IV dataset according to AUC, accuracy and F2 metrics, with respective 95% confidence intervals.

医疗机器学习

临床预测模型

Performance of ML algorithms in MIMIC IV dataset according to AUC, accuracy and F2 metrics, with respective 95% confidence intervals.

Figshare2024-10-11 更新00

Table 1_Joint association of estimated glucose disposal rate and body mass index with new-onset stroke.docx

中风风险预测

肥胖与胰岛素抵抗

BackgroundStroke is a major global health concern, and understanding its modifiable risk factors is critical for prevention. Body mass index (BMI) and estimated glucose disposal rate (eGDR), indicator

NIAID Data Ecosystem00

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

Test for multi-collinearity.

前列腺癌骨转移预测

临床预测模型

BackgroundProstate cancer is the most prevalent male malignancy in Ghana, with a high-risk of metastatic progression. Early detection and adequate disease severity stratification are crucial for timel

Figshare2025-05-28 更新00

Predicting Stroke Risk Dataset

资源简介：

相关数据集