Cuff_less_BP_Prediction | Blood Pressure from ECG and PPG signals using regression

by jeya-maria-jose Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | Cuff_less_BP_Prediction Summary

Cuff_less_BP_Prediction is a Python library. Cuff_less_BP_Prediction has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Cuff_less_BP_Prediction build file is not available. You can download it from GitHub.

Prediction of Blood Pressure from ECG and PPG signals using regression methods.

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Quality

Security

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Support

Cuff_less_BP_Prediction has a low active ecosystem.

It has 51 star(s) with 18 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 6 have been closed. On average issues are closed in 41 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Cuff_less_BP_Prediction is current.

Quality

Cuff_less_BP_Prediction has 0 bugs and 0 code smells.

Security

Cuff_less_BP_Prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Cuff_less_BP_Prediction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Cuff_less_BP_Prediction is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Cuff_less_BP_Prediction releases are not available. You will need to build from source code and install.

Cuff_less_BP_Prediction has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Cuff_less_BP_Prediction saves you 1626 person hours of effort in developing the same functionality from scratch.

It has 3611 lines of code, 232 functions and 56 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Cuff_less_BP_Prediction and discovered the below as its top functions. This is intended to give you an instant insight into Cuff_less_BP_Prediction implemented functionality, and help decide if they suit your requirements.

Forward pass through the convolutional function
Swish with sigmoid
Build a VGG19 model
Create a list of convolutional layers
Construct a VGG model
Create a VGG16 model
Create a VGG model
Compute the convolutional network
Run test
Return an EfficientNet
DPN
Shuffle network
Convenience constructor for Densenet
Factory for the PNASNet class
Setup preact resnet
A basic block of ResNet
Sets a SENet
Test the resnexn
ResNeXT
Create VGG16 model

Get all kandi verified functions for this library.

Cuff_less_BP_Prediction Key Features

No Key Features are available at this moment for Cuff_less_BP_Prediction.

Cuff_less_BP_Prediction Examples and Code Snippets

No Code Snippets are available at this moment for Cuff_less_BP_Prediction.

Community Discussions

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Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Cuff_less_BP_Prediction

You can download it from GitHub.
You can use Cuff_less_BP_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

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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