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monai-deploy

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

https://github.com/project-monai/monai-deploy

Science Score: 36.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 23 committers (8.7%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.9%) to scientific vocabulary

Keywords

ai ai-application-deployment ai-application-development deep-learning dicom fhir guidelines healthcare inference machine-learning medical-imaging ml-platform mlops monai open-standard pathology python pytorch radiology
Last synced: 6 months ago · JSON representation

Repository

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

Basic Info
  • Host: GitHub
  • Owner: Project-MONAI
  • License: apache-2.0
  • Language: Shell
  • Default Branch: main
  • Homepage:
  • Size: 221 MB
Statistics
  • Stars: 105
  • Watchers: 22
  • Forks: 25
  • Open Issues: 29
  • Releases: 7
Topics
ai ai-application-deployment ai-application-development deep-learning dicom fhir guidelines healthcare inference machine-learning medical-imaging ml-platform mlops monai open-standard pathology python pytorch radiology
Created almost 5 years ago · Last pushed 11 months ago
Metadata Files
Readme Contributing License Citation

README.md

project-monai

MONAI Deploy Working Group

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

If you want to know more about its purpose and vision, please review the MONAI Deploy WG wiki.

Focus

MONAI Deploy builds on the foundation set by MONAI.

Where MONAI is focused on training and creating models, MONAI Deploy is focused on defining the journey from research innovation to clinical production environments in hospitals. Our guiding principles are: - Implementation mindset. Create tangible assets: tools, applications and demos/prototypes. - Radiology first, then other modalities like Pathology. - Interoperability with clinical systems. Starting with DICOM, then FHIR. - Central repository to facilitate collaboration among institutions.

Status

MONAI Deploy was released at MICCAI 2021 and was part of the MONAI 2021 Bootcamp. Since then we have released several versions of some of the sub-systems, while others are being actively developed. Please check out the next section.

Key assets

Community

To participate, please join the MONAI Deploy WG weekly meetings on the calendar. All the recordings and meeting notes since day zero can be found at MONAI Deploy WG master doc

Join our Slack channel or join the conversation on Twitter @ProjectMONAI.

Ask and answer questions over on MONAI Deploy's GitHub Discussions tab or MONAI's GitHub Discussions tab.

Links

Owner

  • Name: Project MONAI
  • Login: Project-MONAI
  • Kind: organization

AI Toolkit for Healthcare Imaging

GitHub Events

Total
  • Create event: 1
  • Release event: 1
  • Issues event: 4
  • Watch event: 8
  • Issue comment event: 7
  • Push event: 17
  • Pull request review event: 3
  • Pull request event: 3
  • Fork event: 3
Last Year
  • Create event: 1
  • Release event: 1
  • Issues event: 4
  • Watch event: 8
  • Issue comment event: 7
  • Push event: 17
  • Pull request review event: 3
  • Pull request event: 3
  • Fork event: 3

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 271
  • Total Committers: 23
  • Avg Commits per committer: 11.783
  • Development Distribution Score (DDS): 0.745
Past Year
  • Commits: 3
  • Committers: 1
  • Avg Commits per committer: 3.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Victor Chang v****g@n****m 69
Rahul Choudhury r****g@g****m 45
Joe Batt j****t@a****m 44
David Bericat 6****t 30
J Wyman j****n@n****m 25
JHancox 4****x 9
Risto Haukioja r****a@n****m 8
Piyush Bhatt p****t@n****m 7
Haris Shuaib h****b@g****m 5
M Q m****q@n****m 4
Dana Groff d****f@n****m 4
Ubuntu u****u@i****l 3
kavink k****k@n****m 3
pnahar p****r@n****m 2
Dr. Sidney Bryson s****2@g****m 2
Eric Kerfoot 1****d 2
Jack Schofield j****d@a****m 2
Haris Shuaib m****b@k****k 2
Alex Woodhead 1****o 1
Gigon Bae g****e@n****m 1
Joss Sparkes j****s@g****m 1
Laurence Jackson l****n@k****k 1
Rupesh Sreeraman e****v@g****m 1
Committer Domains (Top 20 + Academic)
nvidia.com: 9 kcl.ac.uk: 2 answerdigital.com: 2 ip-172-31-77-27.ec2.internal: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 54
  • Total pull requests: 88
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 1 month
  • Total issue authors: 23
  • Total pull request authors: 23
  • Average comments per issue: 2.98
  • Average comments per pull request: 0.85
  • Merged pull requests: 80
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 3
  • Pull requests: 3
  • Average time to close issues: 4 days
  • Average time to close pull requests: about 2 hours
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.33
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • ristoh (8)
  • dbericat (6)
  • slbryson (5)
  • AHarouni (4)
  • bluna301 (4)
  • JoeBatt1989 (3)
  • justinhorton2003 (3)
  • IntegratorBrad (2)
  • chezhia (2)
  • whoisj (2)
  • hshuaib90 (2)
  • SameerShanbhogue (2)
  • tomaroberts (1)
  • jordimassaguerpla (1)
  • Bala93 (1)
Pull Request Authors
  • JoeBatt1989 (30)
  • mocsharp (13)
  • dbericat (9)
  • whoisj (6)
  • JHancox (5)
  • hshuaib90 (3)
  • MMelQin (3)
  • ChristianHinge (2)
  • awsjpleger (2)
  • slbryson (2)
  • ristoh (2)
  • gigony (1)
  • KavinKrishnan (1)
  • woodheadio (1)
  • rupeshs (1)
Top Labels
Issue Labels
monai-deploy-express (11) documentation (10) community (9) enhancement (9) guideline (8) feature (5) bug (2) Decision made by WG (2) Need (2) help wanted (2) deploy (1) question (1) build (1)
Pull Request Labels
guideline (16) documentation (13) monai-deploy-express (7) enhancement (7) invalid (5) Decision made by WG (5) community (4) feature (1) deploy (1) help wanted (1) build (1)

Dependencies

.github/workflows/monai-deploy-express.yml actions
  • TheDoctor0/zip-release 0.6.2 composite
  • actions/checkout v3 composite
  • ncipollo/release-action v1.10.0 composite
.github/workflows/test-monai-deploy-express.yml actions
  • actions/checkout v3 composite
deploy/monai-deploy-express/docker-compose.yml docker
  • $ELASTICSEARCH_IMAGE latest
  • $INFORMATICS_GATEWAY_CONFIG_IMAGE latest
  • $INFORMATICS_GATEWAY_IMAGE latest
  • $KIBANA_CONFIG_IMAGE latest
  • $KIBANA_IMAGE latest
  • $LOGSTASH_IMAGE latest
  • $MINIO_IMAGE latest
  • $MONGODB_IMAGE latest
  • $ORTHANC_IMAGE latest
  • $RABBITMQ_IMAGE latest
  • $TASK_MANAGER_IMAGE latest
  • $WORKFLOW_MANAGER_IMAGE latest
demos/ig-tm-map/requirements.txt pypi
  • minio >=7.1
  • pika >=1.2
deploy/monai-deploy-express/platforms/AWS/requirements-dev.txt pypi
  • pytest ==6.2.5 development
deploy/monai-deploy-express/platforms/AWS/requirements.txt pypi
  • aws-cdk-lib ==2.63.0
  • constructs >=10.0.0,<11.0.0