非洲农村地区神经综合征诊断工作:医疗服务提供者的知识、态度和实践

基于定性研究方法,记录刚果农村地区医疗服务提供者对神经综合征诊断的知识、态度和实践。

Figshare
2016-01-15 更新
浏览 15
文本lacksoftware ATLAS.ti.ResultsCare providershealth zonespracticeDemocratic Republiccare providershealth centersresearch approachNeurological SyndromesBandundu ProvincetoolClinical management
Diagnostic Work-Up of Neurological Syndromes in a Rural African Setting: Knowledge, Attitudes and Practices of Health Care Providers

基本信息

模态
文本
大小
0.000200924 GB
许可
CC BY 4.0
创建/更新时间
2016-01-15
版本
v1

资源简介

非洲农村地区神经综合征诊断工作:医疗服务提供者的知识、态度和实践

【数据集背景】

本数据集源站标题为《Diagnostic Work-Up of Neurological Syndromes in a Rural African Setting: Knowledge, Attitudes and Practices of Health Care Providers》。配套论文《Diagnostic Work-Up of Neurological Syndromes in a Rural African Setting: Knowledge, Attitudes and Practices of Health Care Providers》发表于 PLoS ONE(2014),DOI:10.1371/journal.pone.0110167。源站首次发布:2014-10-23。

【数据内容】

源站原始描述:Background Neurological disorders of infectious origin are common in rural sub-Saharan Africa and usually have serious consequences. Unfortunately, these syndromes are often poorly documented for lack of diagnostic tools. Clinical management of these diseases is a major challenge in under-equipped rural health centers and hospitals. We documented health care provider knowledge, attitudes and practices related to this syndrome in two rural health zones in Bandundu Province, Democratic Republic of…

【数据结构与技术规格】

文件数 8 个,合计 200.92 KB。Table_S1.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,22.77 KB。Table_S2.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,22.03 KB。Table_S3.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,21.14 KB。数据集 DOI:10.1371/journal.pone.0110167。

【主题与分类】

源站学科分类:Biological Sciences。主题标签:lack、software ATLAS.ti.ResultsCare providers、health zones、practice、Democratic Republic、care providers、Health Care Providers BackgroundNeurological disorders、health centers、research approach、Neurological Syndromes。

【适用方向】

文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。

【获取与许可】

源站页面:https://plos.figshare.com/articles/dataset/_Diagnostic_Work_Up_of_Neurological_Syndromes_in_a_Rural_African_Setting_Knowledge_Attitudes_and_Practices_of_Health_Care_Providers_/1219815

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Mpanya, Alain; Boelaert, Marleen; Baloji, Sylvain; Matangila, Junior; Lubanza, Symphorien; Bottieau, Emmanuel; et al. (2016). Diagnostic Work-Up of Neurological Syndromes in a Rural African Setting: Knowledge, Attitudes and Practices of Health Care Providers. PLOS ONE. Dataset

【使用注意】

· 源站最后修改于 2023-06-08,引用时请注意版本时效。

官方服务

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⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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下载信息

注册下载

需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。

暂未开放

公开下载

无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。

免登录

有偿下载

公开数据集受托下载与技术交付服务。

提供高速下载与技术交付服务(收技术服务费,非数据销售)

暂未开放

当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。

使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "Table_S1.docx" "https://ndownloader.figshare.com/files/1761417"
curl -L -o "Table_S2.docx" "https://ndownloader.figshare.com/files/1761418"
curl -L -o "Table_S3.docx" "https://ndownloader.figshare.com/files/1761420"
curl -L -o "Text_S1.docx" "https://ndownloader.figshare.com/files/1761422"
curl -L -o "Text_S2.docx" "https://ndownloader.figshare.com/files/1761423"
curl -L -o "Text_S3.docx" "https://ndownloader.figshare.com/files/1761424"
curl -L -o "Text_S4.docx" "https://ndownloader.figshare.com/files/1761425"
curl -L -o "Text_S5.docx" "https://ndownloader.figshare.com/files/1761426"

文件清单

  • Table_S1.docx(22.77 KB)
  • Table_S2.docx(22.03 KB)
  • Table_S3.docx(21.14 KB)
  • Text_S1.docx(31.34 KB)
  • Text_S2.docx(26.49 KB)
  • Text_S3.docx(24.12 KB)
  • Text_S4.docx(25.63 KB)
  • Text_S5.docx(27.41 KB)

文件总体积 200.92 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

Background
Neurological disorders of infectious origin are common in rural sub-Saharan Africa and usually have serious consequences. Unfortunately, these syndromes are often poorly documented for lack of diagnostic tools. Clinical management of these diseases is a major challenge in under-equipped rural health centers and hospitals. We documented health care provider knowledge, attitudes and practices related to this syndrome in two rural health zones in Bandundu Province, Democratic Republic of Congo.
Methods
We used a qualitative research approach combining observation, in-depth interviews and focus group discussions. We observed 20 patient-provider contacts related to a neurological syndrome, conducted 12 individual interviews and 4 focus group discussions with care providers. All interviews were audiotaped and the transcripts were analyzed with the software ATLAS.ti.
Results
Care providers in this region usually limit their diagnostic work-up to clinical examination primarily because of the financial hurdles in this entirely out-of-pocket payment system. The patients prefer to purchase drugs rather than diagnostic tests. Moreover the general lack of diagnostic tools and the representation of the clinician as a “diviner” do not enhance any use of laboratory or other diagnostic methods.
Conclusion
Innovation in diagnostic technology for neurological disorders is badly needed in Central-Africa, but its uptake in clinical practice will only be a success if tools are simple, affordable and embedded in a patient-centered approach.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0110167(source: https://plos.figshare.com/articles/dataset/_Diagnostic_Work_Up_of_Neurological_Syndromes_in_a_Rural_African_Setting_Knowledge_Attitudes_and_Practices_of_Health_Care_Providers_/1219815)。

数据缺失?

依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。

⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

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