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mlni

Machine Learning in NeuroImaging (MLNI) is a python package that performs various tasks using neuroimaging data.

https://github.com/anbai106/mlni

Science Score: 77.0%

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
    Found 8 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: arxiv.org, medrxiv.org, ncbi.nlm.nih.gov, sciencedirect.com, springer.com, nature.com
  • ✓
    Committers with academic emails
    2 of 4 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (10.6%) to scientific vocabulary

Keywords

classification clustering regression
Last synced: 4 months ago · JSON representation ·

Repository

Machine Learning in NeuroImaging (MLNI) is a python package that performs various tasks using neuroimaging data.

Basic Info
Statistics
  • Stars: 18
  • Watchers: 3
  • Forks: 7
  • Open Issues: 1
  • Releases: 1
Topics
classification clustering regression
Created over 5 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

mlni Logo
MLNI

Machine Learning in NeuroImaging

Documentation

MLNI

MLNI is a python package that performs various tasks using neuroimaging data: i) binary classification for disease diagnosis, following good practice proposed in AD-ML; ii) regression prediction, such as age prediction; and iii) semi-supervised clustering with HYDRA.

Citing this work

:warning: Please let me know if you use this package for your publication; I will update your papers in the section of Publication using MLNI...

:warning: Please cite the software using the Cite this repository button on the right sidebar menu, as well as the original papers below for different tasks...

If you use this software for classification:

Wen, J., 2020. Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer’s disease. Neuroinformatics, pp.1-22. doi:10.1007/s12021-020-09469-5 - Paper in PDF

If you use this software for regression:

Wen, J., 2024. The Genetic Architecture of Multimodal Human Brain Age. Nature Communications, pp.1-22. 10.1038/s41467-024-46796-6 - Paper in PDF

The MULTI Consortium., 2025. Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk. 10.1038/s41467-025-59964-z - Paper in PDF

Wen, J., 2025. Refining the generation, interpretation, and application of multi-organ, multi-omics biological aging clocks. Nature Aging. 10.1101/2025.02.06.25321803 - Paper in PDF

If you use this software for clustering:

Varol, E., 2017. HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework. Neuroimage, 145, pp.346-364. doi:10.1016/j.neuroimage.2016.02.041 - Paper in PDF

Publication using MLNI

Wen, J., 2021. Multi-scale semi-supervised clustering of brain images: deriving disease subtypes. MedIA. - Link

Wen, J., 2022. Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression. JAMA Psychiatry - Link

Lalousis, P.A., 2022. Neurobiologically Based Stratification of Recent Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes. Biological Psychiatry. - Link

Wen, J., 2025. Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders. Nature BME. - Link

Owner

  • Name: Junhao (Hao) WEN
  • Login: anbai106
  • Kind: user
  • Location: NYC
  • Company: Columbia University

Medical Imaging Analysis, AI/ML, Multi-omics, Multi-organ

Citation (CITATION.cff) 

abstract: "This is my MLNI software for research purposes only, including classfications, clustering, and regression..."
authors:
  - family-names: Wen
    given-names: Junhao
    orcid: "https://orcid.org/0000-0003-2077-3070"
cff-version: 1.2.0
version: 0.1.5.1
date-released: "2025-05-26"
keywords:
  - "classification, clustering, regression"
  - research
license: MIT
message: "If you use this software, please cite it using these metadata."
repository-code: "https://github.com/anbai106/mlni"
title: "mlni"

GitHub Events

Total
  • Issues event: 4
  • Watch event: 8
  • Issue comment event: 5
  • Push event: 6
  • Pull request event: 2
  • Fork event: 1
Last Year
  • Issues event: 4
  • Watch event: 8
  • Issue comment event: 5
  • Push event: 6
  • Pull request event: 2
  • Fork event: 1

Committers

Last synced: almost 2 years ago

All Time
  • Total Commits: 96
  • Total Committers: 4
  • Avg Commits per committer: 24.0
  • Development Distribution Score (DDS): 0.115
Past Year
  • Commits: 7
  • Committers: 1
  • Avg Commits per committer: 7.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
anbai106 a****6@h****m 85
Hao h****o@c****u 6
Junhao WEN j****9@g****m 4
Abdulkadir, Ahmed a****r@p****u 1
Committer Domains (Top 20 + Academic)
pennmedicine.upenn.edu: 1 cbica-dav-pc01.uphs.upenn.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 8
  • Total pull requests: 3
  • Average time to close issues: 4 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 5
  • Total pull request authors: 2
  • Average comments per issue: 1.88
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 2
  • Average time to close issues: 19 minutes
  • Average time to close pull requests: 4 minutes
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • sourdougie (3)
  • IoannaSkampardoni (2)
  • nimzodisaster (2)
  • yh-zhu (1)
  • cnacc23 (1)
Pull Request Authors
  • kosarah446 (2)
  • AbdulkadirA (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 106 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 16
  • Total maintainers: 1
pypi.org: mlni

Machine Learning in NeuroImaging for various tasks, e.g., regression, classification and clustering.

  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 106 Last month
Rankings
Dependent packages count: 10.1%
Forks count: 14.2%
Average: 19.9%
Dependent repos count: 21.6%
Stargazers count: 25.1%
Downloads: 28.7%
Maintainers (1)
anbai106
Last synced: 5 months ago

Dependencies

requirements.txt pypi
  • matplotlib *
  • nibabel *
  • numpy *
  • pandas *
  • scikit-learn >=0.21.3
setup.py pypi