低风险前列腺癌主动监测列线图数据集

数据集获取（Figshare）

• 源站标题：How to Pick Out the “Unreal” Gleason 3 + 3 Patients: A Nomogram for More Precise Active Surveillance Protocol in Low-Risk Prostate Cancer in a Chinese Population
• DOI：10.6084/m9.figshare.9943988.v1
• 发布日期：2019-10-07
• 文件数：2 个
• 文件总体积：71.30 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/How_to_Pick_Out_the_Unreal_Gleason_3_3_Patients_A_Nomogram_for_More_Precise_Active_Surveillance_Protocol_in_Low-Risk_Prostate_Cancer_in_a_Chinese_Population/9943988

命令行下载

curl -L -o "iivs_a_1669745_sm4730.pdf" "https://ndownloader.figshare.com/files/17907734"
curl -L -o "iivs_a_1669745_sm4724.pdf" "https://ndownloader.figshare.com/files/17907737"

文件清单

• iivs_a_1669745_sm4730.pdf（47.11 KB）
• iivs_a_1669745_sm4724.pdf（24.18 KB）

文件总体积 71.30 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

To develop a nomogram for selecting the “unreal” Gleason score (GS) 3 + 3 patients in biopsy GS 3 + 3 prostate cancer (PCa) patients.
Patients who were newly diagnosed with PCa by biopsy and underwent radical prostatectomy in the First Affiliated Hospital of Nanjing Medical University from January 2009 to October 2018 were enrolled. Comparisons were made between GS 3 + 3 and higher grade PCa patients. Logistic regression analysis was performed to determine the risk factors for the “unreal” GS 3 + 3 PCa in biopsy GS 3 + 3 patients. Then, a nomogram was developed to predict the probability of “unreal” GS 3 + 3 PCa according to the results of multivariate analysis. Finally, receiver operating characteristic and decision curve analysis (DCA) curves were structured to identify the efficiency of the predictive model.
Compared to higher GS grade, biopsy GS 3 + 3 had greater upgrade risk (P P  The nomogram identified the probability of “unreal” GS 3 + 3 PCa in biopsy GS 3 + 3 PCa patients, which was of great value for clinical guidance in low risk PCa therapy.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.9943988.v1（source: https://tandf.figshare.com/articles/dataset/How_to_Pick_Out_the_Unreal_Gleason_3_3_Patients_A_Nomogram_for_More_Precise_Active_Surveillance_Protocol_in_Low-Risk_Prostate_Cancer_in_a_Chinese_Population/9943988）。