基于移动应用的血氧测定：远程医疗中呼吸症状患者适当转诊的潜在工具

数据集获取（Figshare）

• 源站标题：Mobile application-based oximetry: a potential toolfor appropriate referral of patients with respiratory symptoms examined via telemedicine
• DOI：10.6084/m9.figshare.21835600.v1
• 发布日期：2023-01-07
• 文件数：8 个
• 文件总体积：375.32 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Mobile_application-based_oximetry_a_potential_toolfor_appropriate_referral_of_patients_with_respiratory_symptoms_examined_via_telemedicine/21835600

命令行下载

curl -L -o "e9119dee56e530218c3a9a2ef4a4c9e1a47f2c4a.jpg" "https://ndownloader.figshare.com/files/38754406"
curl -L -o "6d30833aedc82a8daf18f99ed427941a0f553eb8.jpg" "https://ndownloader.figshare.com/files/38754409"
curl -L -o "a8d6554322827e259a236ee90d640f03afde4224.jpg" "https://ndownloader.figshare.com/files/38754412"
curl -L -o "0aa70510e4950140cd5e6bf9ceaaf7816cf5be89.jpg" "https://ndownloader.figshare.com/files/38754418"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/38754421"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/38754424"
curl -L -o "Table_3.xls" "https://ndownloader.figshare.com/files/38754427"
curl -L -o "Table_4.xls" "https://ndownloader.figshare.com/files/38754430"

文件清单

• e9119dee56e530218c3a9a2ef4a4c9e1a47f2c4a.jpg（233.38 KB）
• 6d30833aedc82a8daf18f99ed427941a0f553eb8.jpg（2.73 KB）
• a8d6554322827e259a236ee90d640f03afde4224.jpg（113.26 KB）
• 0aa70510e4950140cd5e6bf9ceaaf7816cf5be89.jpg（3.42 KB）
• Table_1.xls（5.63 KB）
• Table_2.xls（5.63 KB）
• Table_3.xls（5.63 KB）
• Table_4.xls（5.63 KB）

文件总体积 375.32 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 Objective To calculate the positive likelihood ratio to determine whether telemedicine is able to optimize referral to the emergency department. Methods Unicenter study with 182 consecutive patients admitted to Hospital Israelita Albert Einstein due to respiratory symptoms. All patients were submitted to oxygen saturation measurement using the standard method Welch Allyn finger device vital sign monitor and a 2-minute evaluation (Binah.ai mobile application). The reproducibility of oxygen saturation measurements made with both methods was investigated using interclass correlation coefficients and analysis of dispersion. Bland-Altman plots were constructed and kappa concordance coefficients used to examine data normality. Accuracy was also estimated. Results Oxygen saturation measurement differences between methods were ≤2% in more than 85% of cases. The mean difference (bias) between methods was near zero (0.835; Bland-Altman analysis). Oxygen saturation measurements made using the Binah.ai mobile application had an average ability to detect patients with altered oxygen saturation levels compared to the conventional method (ROC analysis). The positive likelihood ratio of the mobile application was 6.23. Conclusion Mobile applications for oxygen saturation measurement are accessible user-friendly tools with moderate impact on clinical telemedicine evaluation of patients with respiratory symptoms, and may optimize referral to the emergency department.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.21835600.v1（source: https://scielo.figshare.com/articles/dataset/Mobile_application-based_oximetry_a_potential_toolfor_appropriate_referral_of_patients_with_respiratory_symptoms_examined_via_telemedicine/21835600）。