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psycop-ml-utils

Machine learning utilities for the PSYCOP project.

https://github.com/aarhus-psychiatry-research/psycop-ml-utils

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.6%) to scientific vocabulary

Keywords

healthcare machine-learning psychiatry
Last synced: 10 months ago · JSON representation ·

Repository

Machine learning utilities for the PSYCOP project.

Basic Info
Statistics
  • Stars: 7
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 8
Topics
healthcare machine-learning psychiatry
Created over 4 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Citation

README.md

Misc. PSYCOP utilities

If you're looking for feature generation, see here.

Current priorities are on the Board 🎬.

python versions Code style: black github actions pytest

🔧 Installation

To get started using psycop-ml-utils simply install it using pip by running the following line in your terminal:

poetry add psycop_ml_utils

or using pip:

pip install psycop_ml_utils

For more detailed instructions on installation e.g. including installation for development, see the installation instructions.

🎓 Project

PSYCOP projects which use psycop-ml-utils.

| Project | Publications |  | | -----------------------|----------| ---------------------------------------------------------------------------------- | | Type 2 Diabetes | | Prediction of type 2 diabetes among patients with visits to psychiatric hospital departments |

📖 Documentation

| Documentation | | | -------------------------- | ---------------------------------------------------------------------------------- | | 🎛 API References | The detailed reference for psycop-ml-utils's API. Including function documentation | | 🙋 FAQ | Frequently asked question |

💬 Where to ask questions

| Type | | | ------------------------------ | ---------------------- | | 🚨 Bug Reports | GitHub Issue Tracker | | 🎁 Feature Requests & Ideas | GitHub Issue Tracker | | 👩‍💻 Usage Questions | GitHub Discussions | | 🗯 General Discussion | GitHub Discussions |

Owner

  • Name: PSYCOP, Aarhus Psychiatry Research
  • Login: Aarhus-Psychiatry-Research
  • Kind: organization
  • Location: Aarhus, Denmark

PSYchiatric Clinical Outcome Prediction (PSYCOP). Aarhus University Hospital - Psychiatry

Citation (citation.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Martin"
  given-names: "Bernstorff"
- family-names: "Lasse"
  given-names: "Hansen"
- family-names: "Enevoldsen"
  given-names: "Kenneth"
  orcid: "https://orcid.org/0000-0001-8733-0966"
title: "PSYCOP machine learning utilities"
version: 0.1.1
# doi: 10.5281/zenodo.6675315
date-released: 2022-21-06
url: "https://github.com/Aarhus-Psychiatry-Research/psycop-ml-utils"

GitHub Events

Total
  • Watch event: 1
  • Delete event: 54
  • Push event: 83
  • Pull request review event: 55
  • Pull request event: 103
  • Create event: 50
Last Year
  • Watch event: 1
  • Delete event: 54
  • Push event: 83
  • Pull request review event: 55
  • Pull request event: 103
  • Create event: 50

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 0
  • Total pull requests: 51
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 minutes
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 45
  • Bot issues: 0
  • Bot pull requests: 51
Past Year
  • Issues: 0
  • Pull requests: 40
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 minutes
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 35
  • Bot issues: 0
  • Bot pull requests: 40
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Dependencies

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