改善上呼吸道感染管理和减少抗生素不当使用的策略
本数据集综述了上呼吸道感染管理及减少抗生素滥用的策略,重点关注低收入和中等收入国家。

基本信息
资源简介
改善上呼吸道感染管理和减少抗生素不当使用的策略
【一句话概览】
本数据集是 figshare 公开的文本数据集,收录 1 个文件,主题涵盖 Antibiotics、Antimicrobial resistance、URTIs、Self purchasing、Health policies,可用于医学自然语言处理(实体识别、信息抽取等),CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Ongoing strategies to improve the management of upper respiratory tract infections and reduce inappropriate antibiotic use particularly among lower and middle-income countries: findings and implications for the future》。源站首次发布:2025-02-04。
【数据内容】
源站原始描述:Introduction Antibiotics are indispensable to maintaining human health; however, their overuse has resulted in resistant organisms, increasing morbidity, mortality and costs. Increasing antimicrobial resistance (AMR) is a major public health threat, resulting in multiple campaigns across countries to improve appropriate antimicrobial use. This includes addressing the overuse of antimicrobials for self-limiting infections, such as upper respiratory tract infections (URTIs), particularly in lower-…
【数据结构与技术规格】
文件数 1 个。数据集 DOI:10.25443/smu-za.28210889.v1。
【主题与分类】
源站学科分类:Space sciences not elsewhere classified、Other environmental sciences not elsewhere classified、Sociology of health、Research, science and technology policy、Infectious diseases。主题标签:Antibiotics、Antimicrobial resistance、URTIs、Self purchasing、Health policies、Ambulance care、LMICs。
【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://smu-za.figshare.com/articles/dataset/Ongoing_strategies_to_improve_the_management_of_upper_respiratory_tract_infections_and_reduce_inappropriate_antibiotic_use_particularly_among_lower_and_middle-income_countries_findings_and_implications_for_the_future/28210889
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Godman, Brian; Haque, Mainul; McKimm, Judy; Abu Bakar, Muhamad; Sneddon, Jacqueline; Wale, Janney; et al. (2025). Ongoing strategies to improve the management of upper respiratory tract infections and reduce inappropriate antibiotic use particularly among lower and middle-income countries: findings…
【使用注意】
· 源站最后修改于 2025-02-05,引用时请注意版本时效。
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)
- 源站标题:Ongoing strategies to improve the management of upper respiratory tract infections and reduce inappropriate antibiotic use particularly among lower and middle-income countries: findings and implications for the future
- DOI:10.25443/smu-za.28210889.v1
- 发布日期:2025-02-04
- 文件数:1 个
- 源站页面:https://smu-za.figshare.com/articles/dataset/Ongoing_strategies_to_improve_the_management_of_upper_respiratory_tract_infections_and_reduce_inappropriate_antibiotic_use_particularly_among_lower_and_middle-income_countries_findings_and_implications_for_the_future/28210889
命令行下载
curl -L -o "2?file=20049446" "https://figshare.com/articles/journal_contribution/Ongoing_strategies_to_improve_the_management_of_upper_respiratory_tract_infections_and_reduce_inappropriate_antibiotic_use_particularly_among_lower_and_middle-income_countries_findings_and_implications_for_the_future/11312162/2?file=20049446"
文件清单
2?file=20049446(大小未知)
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
Introduction
Antibiotics are indispensable to maintaining human health; however, their overuse has resulted in resistant organisms, increasing morbidity, mortality and costs. Increasing antimicrobial resistance (AMR) is a major public health threat, resulting in multiple campaigns across countries to improve appropriate antimicrobial use. This includes addressing the overuse of antimicrobials for self-limiting infections, such as upper respiratory tract infections (URTIs), particularly in lower- and middle-income countries (LMICs) where there is the greatest inappropriate use and where antibiotic utilization has increased the most in recent years. Consequently, there is a need to document current practices and successful initiatives in LMICs to improve future antimicrobial use.
Methodology
Documentation of current epidemiology and management of URTIs, particularly in LMICs, as well as campaigns to improve future antimicrobial use and their influence where known.
Results
Much concern remains regarding the prescribing and dispensing of antibiotics for URTIs among LMICs. This includes considerable self-purchasing, up to 100% of pharmacies in some LMICs. However, multiple activities are now ongoing to improve future use. These incorporate educational initiatives among all key stakeholder groups, as well as legislation and other activities to reduce self-purchasing as part of National Action Plans (NAPs). Further activities are still needed however. These include increased physician and pharmacist education, starting in medical and pharmacy schools; greater monitoring of prescribing and dispensing practices, including the development of pertinent quality indicators; and targeted patient information and health education campaigns. It is recognized that such activities are more challenging in LMICs given more limited resources and a lack of healthcare professionals.
Conclusion
Initiatives will grow across LMICs to reduce inappropriate prescribing and dispensing of antimicrobials for URTIs as part of NAPs and other activities, and these will be monitored.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.25443/smu-za.28210889.v1(source: https://smu-za.figshare.com/articles/dataset/Ongoing_strategies_to_improve_the_management_of_upper_respiratory_tract_infections_and_reduce_inappropriate_antibiotic_use_particularly_among_lower_and_middle-income_countries_findings_and_implications_for_the_future/28210889)。
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。




