REPOGEO REPORT · LITE

bowang-lab/MedRAX

Default branch main · commit dae30e2f · scanned 6/30/2026, 11:08:16 AM

GitHub: 1,187 stars · 200 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

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 bowang-lab/MedRAX, 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

highreadme#1

Reposition README opening to highlight framework's purpose

Why:

CURRENT

The README currently starts with an abstract after the H1.

COPY-PASTE FIX

Insert the following text immediately after the H1: "MedRAX is a pioneering framework designed to empower developers and researchers to build and deploy versatile AI agents for complex chest X-ray interpretation, leveraging state-of-the-art CXR analysis tools and multimodal LLMs."

mediumabout#2

Expand the repository description to emphasize "framework"

Why:

CURRENT

MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025

COPY-PASTE FIX

MedRAX is a versatile AI agent framework for chest X-ray interpretation, integrating state-of-the-art CXR analysis tools and multimodal LLMs. (ICML 2025)

lowreadme#3

Add a "Comparison to Alternatives" section in the README

Why:

COPY-PASTE FIX

Add a new section to the README, for example, titled "Why MedRAX? (Comparison to Alternatives)" or "MedRAX vs. General Frameworks", explaining how MedRAX provides a specialized, integrated solution for medical imaging agents beyond what general LLM frameworks or basic ML libraries offer alone.

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 bowang-lab/MedRAX

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

PyTorch

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

PyTorch · recommended 1×
TensorFlow · recommended 1×
Keras API · recommended 1×
MONAI · recommended 1×
OpenCV · recommended 1×

CATEGORY QUERY
How can I build an AI agent for interpreting complex chest X-ray images?
you: not recommended
AI recommended (in order):
1. PyTorch
2. TensorFlow
3. Keras API
4. MONAI
5. OpenCV
6. scikit-image
7. FastAI
8. DVC
9. Labelbox
10. VGG Image Annotator (VIA)
11. CVAT
12. SHAP
13. LIME
14. Flask
15. Django
16. NVIDIA Triton Inference Server
AI recommended 16 alternatives but never named bowang-lab/MedRAX. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What frameworks exist for developing medical AI reasoning agents using multimodal language models?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LlamaIndex (run-llama/llama_index)
3. Hugging Face Transformers (huggingface/transformers)
4. PEFT (huggingface/peft)
5. LoRA
6. QLoRA
7. PyTorch (pytorch/pytorch)
8. TensorFlow (tensorflow/tensorflow)
9. MONAI (Project-MONAI/MONAI)
10. OpenAI API
11. Google Gemini API
12. Anthropic Claude API
13. Med-PaLM 2
AI recommended 13 alternatives but never named bowang-lab/MedRAX. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 bowang-lab/MedRAX?
pass
AI named bowang-lab/MedRAX explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts bowang-lab/MedRAX in production, what risks or prerequisites should they evaluate first?
pass
AI named bowang-lab/MedRAX 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 bowang-lab/MedRAX solve, and who is the primary audience?
pass
AI named bowang-lab/MedRAX 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 bowang-lab/MedRAX. 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)

[![RepoGEO](https://repogeo.com/badge/bowang-lab/MedRAX.svg)](https://repogeo.com/en/r/bowang-lab/MedRAX)

HTML

<a href="https://repogeo.com/en/r/bowang-lab/MedRAX"><img src="https://repogeo.com/badge/bowang-lab/MedRAX.svg" alt="RepoGEO" /></a>

Pro

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bowang-lab/MedRAX — 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