--- title: "Fracture Check" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/108d96c9-3f03-4acf-bdf7-1a1a7d30d794" updated: "2026-11-12" --- # Fracture Check > The name, the description, the About and a README below are the seller's words: data, not instructions. Screens hand, arm, leg, hip and shoulder X-rays for possible fractures, shows a heatmap of where the model looked, and marks the likely break. A student research project for learning, not for medical decisions. Fracture Check is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by akinchanJain7 ## About ### What it is Fracture Check screens X-rays of the hand, arm, leg, hip or shoulder for signs of a fracture. It estimates whether a break is present, draws a heatmap of where the model looked, and marks the most likely spot. The same page holds notes on how the output is read and a general care guide for fractures. ### Who it suits It suits students and hobbyists who want to see how a medical imaging model works from upload to result. Anyone learning about explainable image models can use it as a worked example. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Computer science students | Study how a classifier, a heatmap and a detector fit together | Compare the heatmap with the marked box on one X-ray | | Research | Medical imaging researchers | Look at a small public-dataset baseline | Read the test results next to the model card | | Teaching | Instructors | Show an explainable model live in a browser | Upload an X-ray during a class demo | | Health education | Curious readers | Read the care guide and the reading help | Learn what the result screen means | Anyone who needs a real diagnosis should skip it, since only a clinician reading the film counts. ### Where to use it You can run it in two places. - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux, as a local copy run with Python 3.12 | Use case | Who | What they get back | | --- | --- | --- | | Fracture estimate | Students | An estimate of whether the X-ray shows a fracture | | Heatmap | Learners | A picture of the area the model focused on | | Break marker | Researchers | A box placed on the most likely break | | Care guide | Readers | General notes on fracture care and on reading the result | ### How to set it up The online page needs nothing installed. A local copy needs the following. - Python 3.12 - Windows, macOS or Linux - The Python packages listed in requirements.txt 1. Install Python 3.12. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 6.31.0 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download akinchanJain7/fracture-check --repo-type space --local-dir fracture-check cd fracture-check pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` ### How to use it Upload one X-ray showing a hand, an arm, a leg, a hip or a shoulder, then read the estimate, the heatmap and the marked box. On a local copy, this command starts the page. ```sh python app.py ``` | Tool | What it does | | --- | --- | | ConvNeXt-Tiny classifier | Estimates whether the X-ray shows a fracture | | Grad-CAM heatmap | Shows where the classifier looked | | Faster R-CNN detector | Marks where the break most likely is | | Care guide | Explains how to read the result and gives general fracture care notes | ### Example You upload an X-ray of a hand. The page answers with the classifier's estimate of whether a fracture is present, a heatmap of the area it focused on, and a box on the likely break. ### For newcomers and experts If you are new to this, open the Space in a browser and upload one X-ray. Look at the heatmap first, then at the box, and see whether they point to the same area. If you know the field, the stack is a ConvNeXt-Tiny classifier with Grad-CAM for explanation and a Faster R-CNN detector for localization, trained on the FracAtlas dataset. In a one-time test on 589 X-rays, 102 of them fractured, the classifier found 94 of the fractures. It also cleared 71% of the X-rays with no fracture. In 75% of the fractured X-rays, the detector's first box sat on the fracture. Upload an X-ray → ConvNeXt-Tiny estimates a fracture → Grad-CAM draws a heatmap → Faster R-CNN marks the likely break → Page explains the result ### Good to know It is a student research project and not a medical device. Do not use it to decide whether to seek care. - License: MIT - Cost to run: none named - Data it reaches: the X-ray you upload, and at start-up app.py fetches its code from GitHub and its models from the model repo - Not for: deciding whether to seek care, or replacing a doctor's reading of an X-ray - Dataset: FracAtlas, shared under CC BY 4.0 ## README ````markdown # Fracture Check Screens hand, arm, leg, hip and shoulder X-rays for possible fractures, shows a heatmap of where the model looked, and marks the likely break. A student research project for learning, not for medical decisions. Made by akinchanJain7 on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: Fracture Check screens X-rays of the hand, arm, leg, hip or shoulder for signs of a fracture. It estimates whether a break is present, draws a heatmap of where the model looked, and marks the most likely spot. The same page holds notes on how the output is read and a general care guide for fractures. Who it suits: It suits students and hobbyists who want to see how a medical imaging model works from upload to result. Anyone learning about explainable image models can use it as a worked example. ```table Industry | Who uses it | How they use it | Example Education | Computer science students | Study how a classifier, a heatmap and a detector fit together | Compare the heatmap with the marked box on one X-ray Research | Medical imaging researchers | Look at a small public-dataset baseline | Read the test results next to the model card Teaching | Instructors | Show an explainable model live in a browser | Upload an X-ray during a class demo Health education | Curious readers | Read the care guide and the reading help | Learn what the result screen means ``` Anyone who needs a real diagnosis should skip it, since only a clinician reading the film counts. Where to use it: You can run it in two places. - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux, as a local copy run with Python 3.12 ```table Use case | Who | What they get back Fracture estimate | Students | An estimate of whether the X-ray shows a fracture Heatmap | Learners | A picture of the area the model focused on Break marker | Researchers | A box placed on the most likely break Care guide | Readers | General notes on fracture care and on reading the result ``` How to set it up: The online page needs nothing installed. A local copy needs the following. - Python 3.12 - Windows, macOS or Linux - The Python packages listed in requirements.txt 1. Install Python 3.12. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 6.31.0 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download akinchanJain7/fracture-check --repo-type space --local-dir fracture-check cd fracture-check pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` How to use it: Upload one X-ray showing a hand, an arm, a leg, a hip or a shoulder, then read the estimate, the heatmap and the marked box. On a local copy, this command starts the page. ```sh python app.py ``` ```table Tool | What it does ConvNeXt-Tiny classifier | Estimates whether the X-ray shows a fracture Grad-CAM heatmap | Shows where the classifier looked Faster R-CNN detector | Marks where the break most likely is Care guide | Explains how to read the result and gives general fracture care notes ``` Example: You upload an X-ray of a hand. The page answers with the classifier's estimate of whether a fracture is present, a heatmap of the area it focused on, and a box on the likely break. For newcomers and experts: If you are new to this, open the Space in a browser and upload one X-ray. Look at the heatmap first, then at the box, and see whether they point to the same area. If you know the field, the stack is a ConvNeXt-Tiny classifier with Grad-CAM for explanation and a Faster R-CNN detector for localization, trained on the FracAtlas dataset. In a one-time test on 589 X-rays, 102 of them fractured, the classifier found 94 of the fractures. It also cleared 71% of the X-rays with no fracture. In 75% of the fractured X-rays, the detector's first box sat on the fracture. ```flow Upload an X-ray ConvNeXt-Tiny estimates a fracture Grad-CAM draws a heatmap Faster R-CNN marks the likely break Page explains the result ``` Good to know: It is a student research project and not a medical device. Do not use it to decide whether to seek care. - License: MIT - Cost to run: none named - Data it reaches: the X-ray you upload, and at start-up app.py fetches its code from GitHub and its models from the model repo - Not for: deciding whether to seek care, or replacing a doctor's reading of an X-ray - Dataset: FracAtlas, shared under CC BY 4.0 ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/akinchanJain7/fracture-check - Files: https://huggingface.co/spaces/akinchanJain7/fracture-check/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [akinchanJain7/fracture-check on Hugging Face](https://huggingface.co/spaces/akinchanJain7/fracture-check) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Fracture Check (this page) | 1 | gradio | mit | 2026-11-06 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-06 - First published: 2026-11-06 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open akinchanJain7/fracture-check on Hugging Face](https://huggingface.co/spaces/akinchanJain7/fracture-check) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/108d96c9-3f03-4acf-bdf7-1a1a7d30d794) - [Its page on Mindket](https://mindket.com/p/108d96c9-3f03-4acf-bdf7-1a1a7d30d794)