Name: 恰加斯病的实用诊断算法：关注低资源环境
Creator: 千方医数集科研发现管道
License: CC BY 4.0

基本信息

模态

文本

大小

0.000042453 GB

许可

CC BY 4.0

创建/更新时间

2023-11-18

版本

v1

资源简介

恰加斯病的实用诊断算法：关注低资源环境

【数据集背景】

本数据集源站标题为《Practical diagnostic algorithms for Chagas disease: a focus on low resource settings》。配套论文《Practical diagnostic algorithms for Chagas disease: a focus on low resource settings》发表于 Expert Review of Anti-infective Therapy（2023），DOI：10.1080/14787210.2023.2279110。项目资助方：AGS and JAP would like to acknowledge the support of the GHIT Fund to the [G2020-203] ChagasLAMP project (https://www.ghitfund.org/investment/portfoliodetail/detail/184/en). The work of N.M.-P., J.C.G.-F., and J.G. was supported by the ISCIII project PI18/01054. Our work is also supported by CIBER - Consorcio Centro de. Investigación Biomédica en Red - (CB 2021), Instituto de Salud Carlos III, Ministerio de Ciencia e. Innovación and Unión Europea – NextGenerationEU. We also acknowledge the support from the grant [CEX2018-000806-S] funded by MCIN/AEI/10.13039/501100011033, and support from the Generalitat de Catalunya through the CERCA Program. J.C.G.-F. received support through a fellowship from “la Caixa” Foundation [ID 100010434, fellowship code: LCF/BQ/DI21/11860037]. We also acknowledge the Generalitat of Catalonia Universities and Research Department, Spain [AGAUR: 2021 SGR 01562].。源站首次发布：2023-11-18。

【数据内容】

源站原始描述：Chagas disease, caused by parasite Trypanosoma cruzi, is the most important neglected tropical disease in the Americas. Two drugs are available for treatment, but access to them is challenging, in part due to complex diagnostic algorithms. These are stage-dependent, involve multiple tests, and are ill-adapted to the reality of vast areas where the disease is endemic. Molecular and serologic tools are used to detect acute and chronic infections, with the performance of the latter showing geograph…

【数据结构与技术规格】

文件数 1 个，合计 42.45 KB。ierz_a_2279110_sm4994.xlsx：application/vnd.openxmlformats-officedocument.spreadsheetml.sheet，42.45 KB。数据集 DOI：10.6084/m9.figshare.24586954.v1。

【主题与分类】

源站学科分类：Medicine、Infectious Diseases、Computational Biology。主题标签：Chagas disease、Trypanosoma cruzi、diagnosis、ELISA、RDTs、PCR、LAMP、point-of-care。

【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://tandf.figshare.com/articles/dataset/Practical_diagnostic_algorithms_for_Chagas_disease_a_focus_on_low_resource_settings/24586954

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

规范引用：Practical diagnostic algorithms for Chagas disease: a focus on low resource settings. Taylor & Francis. Gabaldón-Figueira, Juan Carlos; Skjefte, Malia; Longhi, Silvia; Escabia, Elisa; García, Lady Juliette; Ros-Lucas, Albert; et al

【使用注意】

· 源站最后修改于 2024-11-05，引用时请注意版本时效。

原始链接

https://figshare.com/articles/dataset/Practical_diagnostic_algorithms_for_Chagas_disease_a_focus_on_low_resource_settings/24586954

访问原始数据

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付，我们提供全链路闭环服务，让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持？联系我们获取定制方案。

帮我联系

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：Practical diagnostic algorithms for Chagas disease: a focus on low resource settings
DOI：10.6084/m9.figshare.24586954.v1
发布日期：2023-11-18
文件数：1 个
文件总体积：42.45 KB
源站页面：https://tandf.figshare.com/articles/dataset/Practical_diagnostic_algorithms_for_Chagas_disease_a_focus_on_low_resource_settings/24586954

命令行下载

curl -L -o "ierz_a_2279110_sm4994.xlsx" "https://ndownloader.figshare.com/files/43193573"

文件清单

ierz_a_2279110_sm4994.xlsx（42.45 KB）

文件总体积 42.45 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

Chagas disease, caused by parasite Trypanosoma cruzi, is the most important neglected tropical disease in the Americas. Two drugs are available for treatment, but access to them is challenging, in part due to complex diagnostic algorithms. These are stage-dependent, involve multiple tests, and are ill-adapted to the reality of vast areas where the disease is endemic. Molecular and serologic tools are used to detect acute and chronic infections, with the performance of the latter showing geographic differences. Breakthroughs in the development of new diagnostic tools include the validation of a loop-mediated isothermal amplification assay for acute infections (T. cruzi-LAMP), and the regional validation of several rapid diagnostic tests (RDTs) for chronic infection, which simplify testing in resource-limited settings. The literature search was carried out in the MEDLINE database until 1 August 2023.
This review outlines existing algorithms, and proposes new ones focused on point-of-care testing.
Integrating point-of-care testing into existing diagnostic algorithms in certain endemic areas will increase access to timely diagnosis and treatment. However, additional research is needed to validate the use of these techniques across a wider geography, and to better understand the cost-effectiveness of their large-scale implementation.