by wshi83 · Agent Tool · ★ 126
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⚕️EHRAgent🤖 The official repository for the code of the paper "EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records". EHRAgent is an LLM agent empowered with a code interface, to autonomously generate and execute code for complex clinical tasks within electronic health records (EHRs). The project page is available at this link. Features EHRAgent is an LLM agent augmented with tools and medical knowledge, to solve complex tabular reasoning derived from EHRs; Planning with a code interface, EHRAgent enables the LLM agent to formulate a clinical problem-solving process as an executable code plan of action sequences, along with a code executor; We introduce interactive coding between the LLM agent and code executor, iteratively refining plan generation and optimizing code execution by examining environment feedback in depth. Data Preparation We use the EHRSQL benchmark for evaluation. The original dataset is for text-to-SQL tasks, and we have made adaptations to our evaluation. We release our clean and pre-processed version of EHRSQL-EHRAgent data. Please download the data and record the path of the data.
| Stars | 126 |
| Forks | 19 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 69.3760677936236/100 |
| Open Issues | 7 |
| Last Updated | 2024-12-26 |
| Created | 2024-01-07 |
| Platforms | python |
| Est. Tokens | ~3k |
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EhrAgent is [EMNLP'24] EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records. It is categorized as a Agent Tool with 126 GitHub stars.
EhrAgent is primarily written in Python. It covers topics such as ehr, llm, llm-agent.
You can find installation instructions and usage details in the EhrAgent GitHub repository at github.com/wshi83/EhrAgent. The project has 126 stars and 19 forks, indicating an active community.
The top alternatives to EhrAgent on Agent Skills Hub include llama-cpp-agent, edsl, atlas-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.