pediatric-bone-age-prediction | Based on kaggle RSNA Pediatric Bone Age Prediction | Machine Learning library
kandi X-RAY | pediatric-bone-age-prediction Summary
kandi X-RAY | pediatric-bone-age-prediction Summary
pediatric-bone-age-prediction is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Numpy applications. pediatric-bone-age-prediction has no bugs, it has no vulnerabilities and it has low support. However pediatric-bone-age-prediction build file is not available. You can download it from GitHub.
Based on kaggle RSNA Bone Age Prediction from X-Rays.
Based on kaggle RSNA Bone Age Prediction from X-Rays.
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Quality
Security
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Support
pediatric-bone-age-prediction has a low active ecosystem.
It has 36 star(s) with 15 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 0 have been closed. On average issues are closed in 486 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of pediatric-bone-age-prediction is current.
Quality
pediatric-bone-age-prediction has 0 bugs and 0 code smells.
Security
pediatric-bone-age-prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
pediatric-bone-age-prediction code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
pediatric-bone-age-prediction does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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pediatric-bone-age-prediction releases are not available. You will need to build from source code and install.
pediatric-bone-age-prediction has no build file. You will be need to create the build yourself to build the component from source.
pediatric-bone-age-prediction saves you 1320 person hours of effort in developing the same functionality from scratch.
It has 2960 lines of code, 92 functions and 34 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed pediatric-bone-age-prediction and discovered the below as its top functions. This is intended to give you an instant insight into pediatric-bone-age-prediction implemented functionality, and help decide if they suit your requirements.
- ResNet next layer
- Create next convolution block
- Bottleneck block
- Construct a convolution block of convolutions
- Execute training
- Get a single genotype
- Create a pandas dataframe from chestage
- Generate data from keras
- Generate combined generator
- Get boneage data from a csv file
- Yield n elements from iterable
- Builds a Predictor model for a given image
- Construct an ImageSelector model
- Returns a pandas DataFrame of chestage data
- Generates data from Keras
- Extracts the image quality
- Train a Predictor model
- Load data from boneage
- Load train data from a csv file
- Combine multiple images
- Load boneage data
- This function loads a list of images
- Boneage prediction model
- Construct SERES network
- Constructs a SERES network
- Construct SERES
- Get boneage dataframe
- Generate a boneage model
- Create a model for boneage resNet
- Load training data from a csv file
- Saves a list of data to a CSV file
Get all kandi verified functions for this library.
pediatric-bone-age-prediction Key Features
No Key Features are available at this moment for pediatric-bone-age-prediction.
pediatric-bone-age-prediction Examples and Code Snippets
No Code Snippets are available at this moment for pediatric-bone-age-prediction.
Community Discussions
Trending Discussions on pediatric-bone-age-prediction
QUESTION
How to include multiple input tensor in keras.model.fit_generator
Asked 2019-Apr-16 at 03:06
I am a keras rookie and I need some help in working with keras after many days struggling at this problem. Please ask for further information if there is any ambiguity.
Currently, I am trying to modify the code from a link.According to their network model, there are 2 input tensors expected. Now I have trouble including 2 input tensors into the source code provided by them.
Function Boneage_prediction_model() initiates a model of 2 input tensors.
...ANSWER
Answered 2019-Apr-14 at 15:23If I understand you correctly, you want to have two inputs for one network and have one label for the combined output. In the official documentation for the fit_generator there is an example with multiple inputs.
Using a dictionary to map the multiple inputs would result in:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install pediatric-bone-age-prediction
You can download it from GitHub.
You can use pediatric-bone-age-prediction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use pediatric-bone-age-prediction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
MURA dataset: https://stanfordmlgroup.github.io/projects/mura/Chest Xrays dataset on box (full set): https://nihcc.app.box.com/v/ChestXray-NIHCCChest Xrays dataset on kaggle (5% sample): https://www.kaggle.com/nih-chest-xrays/dataBone Age dataset: https://stanfordmedicine.app.box.com/s/4r1zwio6z6lrzk7zw3fro7ql5mnoupcv/folder/42459416739RSNA Bone Age on kaggle: https://www.kaggle.com/kmader/rsna-bone-ageDifferent architectures to try out: https://keras.io/applications/2017 RSNA pediatric bone age challenge: http://rsnachallenges.cloudapp.net/competitions/416Bit challenge winner: https://www.16bit.ai/blog/ml-and-future-of-radiology
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