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Alterlab Pyhealth

技能 已验证 活跃

Part of the AlterLab Academic Skills suite. Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).

目的

To empower researchers and developers with specialized tools and models for advancing machine learning applications in healthcare.

功能

  • Comprehensive healthcare AI toolkit
  • Supports various clinical datasets (MIMIC, eICU, OMOP)
  • Handles diverse prediction tasks (mortality, readmission, drug recommendation)
  • Integrates medical coding systems (ICD, NDC, ATC)
  • Provides interpretable models and fairness metrics

使用场景

  • Developing clinical prediction models
  • Processing electronic health records (EHR)
  • Implementing deep learning for healthcare
  • Analyzing physiological signals and medical images

非目标

  • Replacing clinical judgment
  • Providing direct patient care
  • General-purpose data science outside of healthcare applications

Maintenance

  • info:Dependency ManagementDependencies like PyTorch are mentioned, but there are no explicit measures like lockfiles or version pinning beyond Python version requirements (>=3.7).

Compliance

  • info:GDPRThe skill operates on clinical data, which may contain personal data. While no explicit mention of GDPR sanitization is found, the focus on academic research suggests responsible data handling is implied.

Execution

  • info:Pinned dependenciesDependencies like Python and PyTorch are mentioned with minimum versions, but specific version pinning or lockfiles are not detailed.

安装

npx skills add AlterLab-IEU/AlterLab-Academic-Skills

通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。

质量评分

已验证
95 /100
1 day ago 分析

信任信号

最近提交17 days ago
星标15
许可证MIT
状态
查看源代码

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