Performance of different predictors on the clinical outcome task.

NIAID Data Ecosystem2026-05-02 收录

数据链接：

https://figshare.com/articles/dataset/Performance_of_different_predictors_on_the_clinical_outcome_task_/27902738 数据链接链接失效反馈

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资源简介：

Performance of different predictors on the clinical outcome task.

创建时间：

2024-11-25

多模态智慧网络的基础功能平台多模态混合数据集

多模态网络

性能评估

本数据集为“多模态智慧网络基础功能平台-数据接口”接收到混合模态数据，由使用测试仪表产生，用于评估多模态智慧网络基础功能平台的功能性能等指标。

国家基础学科公共科学数据中心180

Performance metrics with a background class weight of 0.2, 0.5, 1.0, and 1.5 for loss.

类别权重调优

性能评估

With the background weight of 1.5, all the classes have an equal weight. The Std Dev Diff represents the standard deviation over validation sections of the differences of the metrics to the default ba

Figshare2024-03-29 更新10

Data_Sheet_3_Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study.PDF

卒中后症状性颅内出血预测

临床预测模型

BackgroundThis study aimed to compare the performance of different machine learning models in predicting symptomatic intracranial hemorrhage (sICH) after thrombolysis treatment for ischemic stroke. Me

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

Table 1_Machine learning-based prediction of intensive care unit admission in COVID-19 patients presenting with mild respiratory failure.docx

COVID-19重症监护预测

临床预测模型

IntroductionPrevious studies applying machine learning to predict severe respiratory failure in COVID-19 patients have shown inconsistent results due to variations in study populations and predictor v

NIAID Data Ecosystem00

Performance of different predictors on the clinical outcome task.

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