预测血管造影识别Adamkiewicz动脉可能性的临床模型开发

数据集获取（Figshare）

• 源站标题：Development of a clinical model to predict the likelihood of identification of the Adamkiewicz artery by angiotomography
• DOI：10.6084/m9.figshare.6273740.v1
• 发布日期：2018-05-16
• 文件数：6 个
• 文件总体积：2.85 MB
• 源站页面：https://scielo.figshare.com/articles/dataset/Development_of_a_clinical_model_to_predict_the_likelihood_of_identification_of_the_Adamkiewicz_artery_by_angiotomography/6273740

命令行下载

curl -L -o "1677-5449-jvb-17-1-19-gf01-en.jpg" "https://ndownloader.figshare.com/files/11469317"
curl -L -o "1677-5449-jvb-17-1-19-gf02-en.jpg" "https://ndownloader.figshare.com/files/11469326"
curl -L -o "1677-5449-jvb-17-1-19-gf03-en.jpg" "https://ndownloader.figshare.com/files/11469335"
curl -L -o "1677-5449-jvb-17-1-19-gf04-en.jpg" "https://ndownloader.figshare.com/files/11469347"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/11469353"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/11469356"

文件清单

• 1677-5449-jvb-17-1-19-gf01-en.jpg（1.11 MB）
• 1677-5449-jvb-17-1-19-gf02-en.jpg（766.21 KB）
• 1677-5449-jvb-17-1-19-gf03-en.jpg（241.18 KB）
• 1677-5449-jvb-17-1-19-gf04-en.jpg（723.12 KB）
• Table_1.xls（5.63 KB）
• Table_2.xls（5.63 KB）

文件总体积 2.85 MB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Abstract Background There are clinically important morphological differences in the Adamkiewicz artery (AKA) between populations that do and do not have aortic disease and they have an influence on the neuroischemic complications involving the spinal cord during surgical operations. It is not yet known whether clinical parameters correlate with the predictability of identification of the artery using angiotomography. Objective To develop a mathematical model that by correlating clinical parameters with atherosclerosis enables prediction of the probability of identification of the AKA in patients examined with angiotomography. Method This is a cross-sectional, observational study using a patient database and image bank. A multivariate statistical analysis was conducted and a logit mathematical model was constructed to predict AKA identification. Significant variables were used to build a formula for calculation of the probability of identification. This model was calibrated and its power of discrimination was assessed using receiver operating characteristic (ROC) curves. Selection of explanatory variables was based on largest area under the ROC curve (p = 0.041) and combined significance of variables. Results A total of 110 cases were analyzed (54.5% were male, mean age was 60.97 years, and ethnicity coefficients were white -2.471, brown -1.297, and black -0.971) and the AKA was identified in 60.9%. Body mass index: 27.06 ± 0.98 (coef. -0.101); smokers: 55.5% (coef. -1.614/-1.439); diabetes: 13.6%; hypertension: 65.5% (coef. -1.469); dyslipidemia: 58.2%; aortic aneurysm: 38.2%; aortic dissection: 12.7%; and mural thrombus: 24.5%. The constant was 6.262. The formula for calculating the probability of detection is as follows: ( e − ( C o e f . E t n i c i t y + ( C o e f . B M I × B M I ) + C o e f . s m o ker + C o e f . S A H + C o e f . d y s l i p + C o n s tan t ) + 1 ) − 1 . The prediction model was constructed and made available at: https://vascular.pro/aka-model . Conclusions Using the covariates ethnicity, body mass index, smoking, arterial hypertension, and dyslipidemia, it proved possible to create a mathematical model for predict

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.6273740.v1（source: https://scielo.figshare.com/articles/dataset/Development_of_a_clinical_model_to_predict_the_likelihood_of_identification_of_the_Adamkiewicz_artery_by_angiotomography/6273740）。