脂肿筛查问卷及筛查模型开发数据集

数据集获取（Figshare）

• 源站标题：Development of a questionnaire and screening model for lipedema
• DOI：10.6084/m9.figshare.14286347.v1
• 发布日期：2021-03-24
• 文件数：5 个
• 文件总体积：1.42 MB
• 源站页面：https://scielo.figshare.com/articles/dataset/Development_of_a_questionnaire_and_screening_model_for_lipedema/14286347

命令行下载

curl -L -o "1677-5449-jvb-19-e20200114-gf01-en.jpg" "https://ndownloader.figshare.com/files/27146618"
curl -L -o "1677-5449-jvb-19-e20200114-gf02-en.jpg" "https://ndownloader.figshare.com/files/27146624"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/27146630"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/27146633"
curl -L -o "Table_3.xls" "https://ndownloader.figshare.com/files/27146636"

文件清单

• 1677-5449-jvb-19-e20200114-gf01-en.jpg（721.30 KB）
• 1677-5449-jvb-19-e20200114-gf02-en.jpg（670.44 KB）
• Table_1.xls（13.82 KB）
• Table_2.xls（5.63 KB）
• Table_3.xls（5.63 KB）

文件总体积 1.42 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 Lipedema is greatly underdiagnosed and there is a lack of low-cost tools to facilitate diagnostic. We created a lipedema screening questionnaire based on a questionnaire for assessing symptoms. Objectives The study objectives were to identify relevant clinical questions, develop a screening questionnaire, and construct a model for predicting lipedema. Method A simplified questionnaire was constructed and administered to a sample of patients with and without lipedema and then the probability of correct diagnosis was analyzed. Results All 109 patients who answered the questionnaire were female and all of them understood the questions. A predictive model using individual question scores achieved an excellent probability of correct diagnosis, at 91.2%, and a predictive model based on total score also achieved a good probability of correct diagnosis, at 86.15%. Conclusions The lipedema screening questionnaire is a practical instrument that is quick and easy to administer and can be used with our population for identification of possible lipedema patients, raising the level of suspicion when taking a patient’s history and conducting a physical examination.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.14286347.v1（source: https://scielo.figshare.com/articles/dataset/Development_of_a_questionnaire_and_screening_model_for_lipedema/14286347）。