# zhihao-chen/QASystemOnMedicalGraph

该项目是基于医疗领域知识图谱的问答系统。实现比较简单。

Repository: https://github.com/zhihao-chen/QASystemOnMedicalGraph
Canonical: https://ross.abutalabs.com/products/qasystemonmedicalgraph
Language: Python
License Family: other
Last push: 2019-05-24T04:53:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2784, "days_push": 2658, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1426, forks 342 (observed 2026-08-28T04:04:41.582316+00:00)

## What it is
A medical-domain knowledge graph question answering system built in Python with Neo4j, containing ~37k entities and ~210k relations scraped from 39 Health. It parses user questions, classifies intent, and answers queries about diseases, symptoms, drugs, and treatments.

## Use cases
- build a medical knowledge graph question answering system
- learn how KBQA pipelines work end to end
- query diseases by symptom, drug, or department
- construct a Neo4j knowledge graph from scraped health data
- implement Chinese question intent classification

## When to choose
- you want a simple, educational reference implementation of a knowledge-graph QA system
- you need a small Chinese medical knowledge graph with Neo4j
- you are learning KBQA intent classification and graph querying

## When to avoid
- you need production-grade medical advice or up-to-date clinical data
- you require a maintained project with a license or active releases
- you need large-scale or multilingual knowledge graphs

## Facets
- artifact type: application
- maturity: maintenance
- function: nlp, search-engine, chatbot, rag
- domain: healthcare, artificial-intelligence, databases
- platform: python, windows
- tags: knowledge-graph, kbqa, neo4j, medical-qa, chinese-nlp, question-answering, natural-language-processing, linux, macos

## Member repositories
- zhihao-chen/QASystemOnMedicalGraph (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.582316+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:37:29.435697+00:00, confidence not recorded.
  - readme: https://github.com/zhihao-chen/QASystemOnMedicalGraph (fetched 2026-08-28T04:04:41.582316+00:00, sha 3eb9e2b4f947)
- Data as of 2026-08-30T08:39:29.467469+00:00.