# liuhuanyong/QASystemOnMedicalKG

A tutorial and implement of disease centered Medical knowledge graph and qa system based on it。知识图谱构建，自动问答，基于kg的自动问答。以疾病为中心的一定规模医药领域知识图谱，并以该知识图谱完成自动问答与分析服务。

Repository: https://github.com/liuhuanyong/QASystemOnMedicalKG
Canonical: https://ross.abutalabs.com/products/qasystemonmedicalkg
Language: Python
License Family: other
Last push: 2024-08-08T07:55:05+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": 2890, "days_push": 755, "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 7363, forks 2279 (observed 2026-08-28T04:09:58.511827+00:00)

## What it is
A tutorial-style Python project that builds a disease-centered medical knowledge graph (44k entities, 300k relations) in Neo4j from scraped vertical medical website data, and implements a question-answering chatbot on top of it. It covers the full pipeline from data collection and dictionary-based entity extraction to graph import and intent-based question parsing.

## Use cases
- build a medical knowledge graph from scratch
- question answering over a knowledge graph
- learn how to construct a domain knowledge graph with neo4j
- medical chatbot that answers disease, drug, and symptom questions
- extract structured medical entities from web data
- tutorial on knowledge graph construction and QA

## When to choose
- you want an end-to-end educational example of building and querying a domain knowledge graph
- you need a Chinese-language medical QA demo based on Neo4j
- you are learning NLP pipelines for entity extraction and question classification

## When to avoid
- you need production-grade, clinically validated medical information
- you need a scalable multi-user QA service with modern LLM-based understanding
- you need a maintained library with a license and active development

## Facets
- artifact type: application
- maturity: maintenance
- function: nlp, search-engine, chatbot, web-scraping, parser
- domain: healthcare, artificial-intelligence, databases
- platform: python, self-hosted
- tags: knowledge-graph, neo4j, question-answering, medical, tutorial, chinese-nlp, natural-language-processing

## Member repositories
- liuhuanyong/QASystemOnMedicalKG (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:58.511827+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 2026-08-29T17:38:24.742353+00:00, confidence not recorded.
  - readme: https://github.com/liuhuanyong/QASystemOnMedicalKG (fetched 2026-08-28T04:09:58.511827+00:00, sha 906fd3b0afab)
- Data as of 2026-08-30T08:39:29.467469+00:00.