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Published 2024 | Version v3
Software Open

Machine learning-based pulse wave analysis for classification of circle of Willis topology: an in silico study with 30,618 virtual subjects

Creators

  • 1. École Nationale Supérieure des Mines
  • 2. ROR icon Universitat Politècnica de Catalunya
  • 3. ROR icon International Center for Numerical Methods in Engineering
  • 4. University of Cambridge (School of Clinical Medicine)
  • 5. TU Wien
  • 6. King's College London

Description

Overview

This repository contains the new dataset described in the article with the same name, MATLAB and Python codes for post-processing the dataset, and the code for training and testing all machine learning models using the open-source library TensorFlow 2.12, the Keras application programming interface, and the Scikit-learn Python package. The dataset includes pulse waves from 30,618 virtual healthy subjects, aged between 25 and 75 years (in 10-year increments), representing seven different circle of Willis topologies.
 
 

Created Databases for each circle of Willis topology

Complete CoW: https://zenodo.org/records/11397985

Missing ACA A1: https://zenodo.org/records/11449121

Missing ACoA: https://zenodo.org/records/11473121

Missing PCA P1: https://zenodo.org/records/11565240

Missing PCoAs: https://zenodo.org/records/11573814

Missing PCoA and PCA P1: https://zenodo.org/records/11567853

Missing PCoA: https://zenodo.org/records/11571907

 

Data Description

The database contains the following waves:

  • arterial flow velocity (U),
  • luminal area (A),
  • pressure (P), and
  • photoplethysmogram (PPG).

These pulse waves are provided at a range of measurement sites, including:

  • aorta (ascending and descending)
  • carotid artery
  • brachial artery
  • radial artery
  • finger
  • femoral artery

The created data are available in three formats: Matlab, CSV and WaveForm Database (WFDB) format. Further details of the formatting and contents of each file are available at: https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database

Accompanying Publication

The database is described in the following publication: https://doi.org/10.1016/j.bspc.2024.106999

 

 

Files

Ml_codes.zip

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Additional details

Related works

Is published in
Journal: https://www.sciencedirect.com/science/article/pii/S1746809424010577 (URL)

Dates

Available
2024