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Machine learning and data analysis for fertility

Project description

Open Ferlility logo

Open Fertility is an open-source project dedicated to advancing fertility analysis and prediction through machine learning. The goal is to foster a community-driven initiative that empowers fertility professionals, researchers, and enthusiasts.

Inspired by the paper An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization the aim is to leverage the open data they published to develop initial models.

The primary objectives are to:

  • Cultivate an inclusive and collaborative community, bringing together experts and enthusiasts.
  • Provide comprehensive tools for training, evaluating, and applying machine learning techniques.
  • Effective data visualization, to gain valuable insights and interpret data with clarity.
  • Deliver intuitive user interfaces that grant easy access to the models.

Get in touch if you feel interested in participating!


During this early develoment stage, a pip install is still not provided.

So, follow these steps:

  1. Download or clone the files
  2. Navigate to the directory containing the repository
  3. Run pip install .

Early features

Download the blastocyst dataset

import openfertility as of

blasto2k = of.datasets.blasto2k.Dataset()

Project details

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openfertility-0.1.0.tar.gz (4.4 kB view hashes)

Uploaded Source

Built Distribution

openfertility-0.1.0-py3-none-any.whl (5.7 kB view hashes)

Uploaded Python 3

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