数据表1：胸部超声、胸部X光和计算机辅助诊断在低资源环境下诊断结核病的比较有效性：埃塞俄比亚横断面研究方案

数据集获取（Figshare）

• 源站标题：Data Sheet 1_Comparative effictiveness of chest ultrasound, chest X-ray and computer-aided diagnostic (CAD) for tuberculosis diagnosis in low-resource setting: study protocol for a cross-sectional study from Ethiopia.pdf
• DOI：10.3389/fpubh.2024.1476866.s001
• 发布日期：2024-11-28
• 文件数：1 个
• 文件总体积：73.13 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Comparative_effictiveness_of_chest_ultrasound_chest_X-ray_and_computer-aided_diagnostic_CAD_for_tuberculosis_diagnosis_in_low-resource_setting_study_protocol_for_a_cross-sectional_study_from_Ethiopia_pdf/27923877

命令行下载

curl -L -o "Data Sheet 1_Comparative effictiveness of chest ultrasound, chest X-ray and computer-aided diagnostic (CAD) for tuberculosis diagnosis in low-resource.pdf" "https://ndownloader.figshare.com/files/50857569"

文件清单

• Data Sheet 1_Comparative effictiveness of chest ultrasound, chest X-ray and computer-aided diagnostic (CAD) for tuberculosis diagnosis in low-resource.pdf（73.13 KB）

文件总体积 73.13 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

IntroductionEarly and accurate diagnosis of pulmonary tuberculosis (TB) is crucial for timely treatment and prevention of transmission, but diagnostic challenges persist due to complex symptoms and limitations in diagnostic tools. Chest X-ray (CXR) is the standard imaging modality, but its sensitivity and specificity may vary. Recently, some promising alternatives emerged such as chest ultrasonography (CUS) – particularly valuable in resource-limited settings – and computer-aided diagnosis (CAD) systems – helping clinicians in the reading and interpretation of the CXR. However, direct comparisons of CUS, CXR, and CAD score in TB diagnosis are limited.
Methods and analysisThis cross-sectional study will assess the diagnostic effectiveness of CUS in diagnosing TB compared to CXR and CAD score among index cases and household contacts. The study will be conducted at Wolisso St. Luke Hospital (Wolisso, Ethiopia). Index cases will be subjects with diagnosis of pulmonary tuberculosis within 7 days. Household contacts will be identified by administering a screening questionnaire to index cases. They will undergo CXR as for standard of care and consequent CAD analysis and CUS. The anticipated sample size is 136 subjects. The common accuracy metrics (sensitivity, specificity, positive and negative predictive values) will be calculated.
Ethics and disseminationThe protocol was approved by the Oromia Health Bureau Research Ethics Committee (BFO/MBTFH/1-16/1908). All information obtained will be confidential. Selected investigators will have access to data, while international partners will sign a dedicated Data Protection Agreement. Eligible subjects will receive a brief information about the study before being asked to participate and they will provide a written informed consent. Results will be conveyed to stakeholders and disseminated through conferences and peer-reviewed journals.
Clinical trial registrationNCT06409780, https://clinicaltrials.gov.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fpubh.2024.1476866.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Comparative_effictiveness_of_chest_ultrasound_chest_X-ray_and_computer-aided_diagnostic_CAD_for_tuberculosis_diagnosis_in_low-resource_setting_study_protocol_for_a_cross-sectional_study_from_Ethiopia_pdf/27923877）。