移动直接观察疗法（MDOT）——一项快速系统评价和哮喘儿童试点研究

数据集获取（Figshare）

• 源站标题：Mobile direct observation of therapy (MDOT) - A rapid systematic review and pilot study in children with asthma
• DOI：10.1371/journal.pone.0190031
• 发布日期：2018-02-05
• 文件数：4 个
• 文件总体积：428.77 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Mobile_direct_observation_of_therapy_MDOT_-_A_rapid_systematic_review_and_pilot_study_in_children_with_asthma/5855013

命令行下载

curl -L -o "S1 PRISMA Checklist.doc" "https://ndownloader.figshare.com/files/10399989"
curl -L -o "S1 CONSORT Checklist.doc" "https://ndownloader.figshare.com/files/10399992"
curl -L -o "S1 Flow.doc" "https://ndownloader.figshare.com/files/10399998"
curl -L -o "S1 Protocol.docx" "https://ndownloader.figshare.com/files/10400010"

文件清单

• S1 PRISMA Checklist.doc（64.00 KB）
• S1 CONSORT Checklist.doc（221.18 KB）
• S1 Flow.doc（61.95 KB）
• S1 Protocol.docx（81.64 KB）

文件总体积 428.77 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

We describe, for the first time, the use of a mobile device platform for remote direct observation of inhaler use and technique. The research programme commenced with a rapid systematic review of mobile device (or videophone) use for direct observation of therapy (MDOT). Ten studies (mainly pilots) were identified involving patients with tuberculosis, sickle cell disease and Alzheimer’'s disease. New studies are ongoing (ClinicalTrials.gov website) in TB, stroke, sickle cell disease, HIV and opioid dependence. Having identified no prior use of MDOT in inhaler monitoring, we implemented a feasibility study in 12 healthy volunteer children (2–12 years; 8 females and 4 males) over a period of 14 days, with twice daily video upload of their ‘‘dummy’’ inhaler use. Two children uploaded 100% of the requested videos, with only one child having an inhaler upload rate of 0.05), however, mean fraction of exhaled nitric oxide (FeNO) values normalised (mean 38.7 to 19.3ppm) and mean Asthma Control Test values improved (13.1 to mean 17.8). Feedback from participants was positive. Overall the findings open up a new paradigm in device independent (can be used for any type of inhaler device) monitoring, providing a platform for evaluating / improving inhaler use at home.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0190031（source: https://plos.figshare.com/articles/dataset/Mobile_direct_observation_of_therapy_MDOT_-_A_rapid_systematic_review_and_pilot_study_in_children_with_asthma/5855013）。