射血分数保留的心力衰竭表型映射

数据集获取（Figshare）

• 源站标题：Phenotype mapping of heart failure with preserved ejection fraction
• DOI：10.6084/m9.figshare.7510082.v1
• 发布日期：2018-12-26
• 文件数：5 个
• 文件总体积：728.85 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Phenotype_mapping_of_heart_failure_with_preserved_ejection_fraction/7510082

命令行下载

curl -L -o "2359-4802-ijcs-20180047-gf01.jpg" "https://ndownloader.figshare.com/files/13930373"
curl -L -o "2359-4802-ijcs-20180047-gf02.jpg" "https://ndownloader.figshare.com/files/13930376"
curl -L -o "2359-4802-ijcs-20180047-gf03.jpg" "https://ndownloader.figshare.com/files/13930379"
curl -L -o "2359-4802-ijcs-20180047-gf04.jpg" "https://ndownloader.figshare.com/files/13930385"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/13930391"

文件清单

• 2359-4802-ijcs-20180047-gf01.jpg（121.93 KB）
• 2359-4802-ijcs-20180047-gf02.jpg（93.15 KB）
• 2359-4802-ijcs-20180047-gf03.jpg（189.88 KB）
• 2359-4802-ijcs-20180047-gf04.jpg（318.26 KB）
• Table_1.xls（5.63 KB）

文件总体积 728.85 KB（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 Heart failure with preserved ejection fraction (HFPEF) has become the main phenotypic model of heart failure (HF) in community and referral patients in Brazil and in the world. Despite advances in the development of new drugs for HF treatment, there has been no significant improvement in mortality of this condition. According to many studies, this can be explained by the heterogeneous nature of HF physiopathology, whose basic mechanisms may result in different clinical presentations, culminating in the emerging of different phenogroups in this syndrome. In this context, phenotype mapping of HFPEF has emerged as a possible solution, since it enables the development of clinical trials that establish specific therapeutic strategies for each phenotypic profile. New technologies in the field of artificial intelligence have enabled the assessment of a large volume of data and infer intrinsic patterns and different outcomes. Thereby, it is possible to obtain mutually exclusive categories of HFPEF, with a phenotype mapping of the syndrome and grouping of patients according to their phenotypic features. Besides, other diseases can have the same clinical phenotype but different pathophysiological basis, the so called “phenocopies”. These tools enable the analysis and categorization of the wide spectrum of heart failure, contributing to solve the dilemmas of the treatment of this syndrome.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.7510082.v1（source: https://scielo.figshare.com/articles/dataset/Phenotype_mapping_of_heart_failure_with_preserved_ejection_fraction/7510082）。