Health Gym

Health Gym包含多个合成医疗数据集,覆盖急性低血压、败血症和HIV场景,用于机器学习特别是强化学习算法的原型化与评估。

arXiv
2022-03-12 更新
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表格败血症表格数据
Health Gym

基本信息

模态
表格
创建/更新时间
2022-03-12

资源简介

Health Gym

【数据集背景】

本数据集源站标题为《arXiv Query: search_query=&id_list=2203.06369v1&start=0&max_results=1》。源站首次发布:2022-03-12。

【数据内容】

源站原始描述:In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not openly available due to their highly confidential nature. This has hampered the development of reproducible and generalisable machine learning applications in health care. Here we introduce the Health Gym - a growing collection of highly realistic synthetic medical datasets that can be freely accessed to prototype, evalua…

【主题与分类】

主题标签:cs.LG。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://arxiv.org/abs/2203.06369v1

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。

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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。

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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

数据集说明

本数据集 对应论文数据集(arXiv 预印本)。

数据获取指引

  1. 打开论文页面获取作者与项目信息:https://arxiv.org/abs/2203.06369v1
  2. 论文 Data Availability / Code Availability 章节标注了数据实际托管位置;
  3. 获取到实际数据链接后,按对应平台标准方式下载。

论文摘要:Abstract:In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not openly available due to their highly confidential nature. This has hampered the development of reproducible and generalisable machine learning applications in health care. Here we introduce the Health Gym - a growing collection of highly realistic synthetic medical datasets that can be freely accessed to prototype, evaluate, and compare machine learning algorithms, with a specific focus on reinforcement learning. The three synthetic datasets described in this paper present patient cohorts with acute hypotension and sepsis in the intensive care unit, and people with human immunodeficiency virus (HIV) receiving antiretroviral therapy in ambulatory care. The datasets were created using a novel generative adversarial network (GAN). The distributions of variables, and correlations between variables and trends over time in the synthetic datasets mirror those in the real datasets. Furthermore, the risk of sensitive information disclosure associated with the public distribution of the synthetic datasets is estimated to be very low.

论文页面:https://arxiv.org/abs/2203.06369v1

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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