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资源简介：
Complete blood count.
应用场景：
创建时间：
2017-12-22
相关数据集
Positive rate of the coagulation parameters between the healthy control and COVID-19 patients.
Positive rate of the coagulation parameters between the healthy control and COVID-19 patients.
Figshare2020-10-29 更新60
Replication Data for: A multi-analyte machine learning model to detect wrong blood in tube errors
Misidentification of blood specimens is an important pre-analytical risk that can lead to patient harm. We developed several machine learning models to detect this problem using Complete Blood Count (
NIAID Data Ecosystem10
Substance concentrations in venous blood.
Means ± SE. Significance levels indicated like for Table 2. MCHC and [Cl−]ery corrected for 2% and 10% trapped plasma, respectively. *14.8±0.5 without the patient with the G551D mutation.
NIAID Data Ecosystem40
Baseline full blood count, liver function test and INR results at presentation.
Baseline full blood count, liver function test and INR results at presentation.
NIAID Data Ecosystem20
