RRepoGEO

REPOGEO REPORT · LITE

ZJU4HealthCare/HealthGPT

Default branch main · commit 9a8a8b29 · scanned 6/22/2026, 12:37:44 PM

GitHub: 1,640 stars · 240 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ZJU4HealthCare/HealthGPT, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add comprehensive topics for medical AI and multimodal LLMs

    Why:

    COPY-PASTE FIX
    medical-ai, multimodal-llm, large-language-model, medical-vision, medical-nlp, healthcare-ai, deep-learning, vision-language-model, icml-2025
  • mediumreadme#2
    Add a concise problem statement and value proposition to the README's opening

    Why:

    CURRENT
    **HealthGPT Series** is a medical multimodal large language model (MLLM) family composed of two subrepositories:
    COPY-PASTE FIX
    The HealthGPT Series provides state-of-the-art medical large vision-language models (LVLMs) designed to unify comprehension and generation across diverse medical data, including text, 2D images, and 3D volumes, addressing the critical need for advanced, specialized AI in healthcare.

**HealthGPT Series** is a medical multimodal large language model (MLLM) family composed of two subrepositories:
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://lin-tianwei.github.io/healthgpt-pro.github.io/

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface ZJU4HealthCare/HealthGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Med-PaLM 2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Med-PaLM 2 · recommended 2×
  2. GPT-4V · recommended 2×
  3. Llama 2 · recommended 2×
  4. BLIP-2 · recommended 1×
  5. InstructBLIP · recommended 1×
  • CATEGORY QUERY
    What AI models can help unify medical image analysis with text generation?
    you: not recommended
    AI recommended (in order):
    1. Med-PaLM 2
    2. GPT-4V
    3. BLIP-2
    4. InstructBLIP
    5. Llama 2
    6. CLIP
    7. DINOv2
    8. ViLT
    9. CoCa
    10. Hugging Face Transformers Library
    11. ViT-GPT2
    12. LayoutLMv3

    AI recommended 12 alternatives but never named ZJU4HealthCare/HealthGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a large language model capable of analyzing medical text, 2D images, and 3D volumes.
    you: not recommended
    AI recommended (in order):
    1. Med-PaLM 2
    2. GPT-4V
    3. Llama 2
    4. BioMed-CLIP
    5. MONAI (Project-MONAI/MONAI)

    AI recommended 5 alternatives but never named ZJU4HealthCare/HealthGPT. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of ZJU4HealthCare/HealthGPT?
    pass
    AI named ZJU4HealthCare/HealthGPT explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ZJU4HealthCare/HealthGPT in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ZJU4HealthCare/HealthGPT explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo ZJU4HealthCare/HealthGPT solve, and who is the primary audience?
    pass
    AI named ZJU4HealthCare/HealthGPT explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of ZJU4HealthCare/HealthGPT. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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ZJU4HealthCare/HealthGPT — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite