outreach_ppi

Outreach and PPI resources for explaining AI to the public

https://github.com/neelsoumya/outreach_ppi

Science Score: 57.0%

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    Found 6 DOI reference(s) in README
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    Low similarity (8.5%) to scientific vocabulary

Keywords

ai artificial-intelligence deep-learning machine-learning materials outreach outreach-ppi patient-public-involvement patients teaching-resources
Last synced: 6 months ago · JSON representation ·

Repository

Outreach and PPI resources for explaining AI to the public

Basic Info
  • Host: GitHub
  • Owner: neelsoumya
  • License: gpl-3.0
  • Default Branch: main
  • Homepage:
  • Size: 7.99 MB
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  • Forks: 1
  • Open Issues: 0
  • Releases: 9
Topics
ai artificial-intelligence deep-learning machine-learning materials outreach outreach-ppi patient-public-involvement patients teaching-resources
Created about 5 years ago · Last pushed almost 3 years ago
Metadata Files
Readme Contributing Funding License Citation

README.md

Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies

Introduction

This repository has open source outreach and patient and public involvement (PPI) resources for increasing awareness of Artificial Intelligence (AI) in healthcare. These resources can be used for teaching AI to the general public and patients.

Resources

  • Resources

    • https://teachablemachine.withgoogle.com/
* https://www.aimyths.org/
  • Tensorflow and AI in the browser

    • https://github.com/tensorflow/tfjs/blob/master/GALLERY.md
    • https://coconet.glitch.me/
    • http://cabreraalex.com/interactive-classification/
    • https://github.com/poloclub/ganlab/
    • https://www.tensorflow.org/js/demos/
    • https://experiments.withgoogle.com/collection/creatability
  • An interactive animation to help understand how neural networks work

    • https://ncase.me/neurons/
  • More AI in the browser and outreach materials

    • http://projector.tensorflow.org/
    • https://experiments.withgoogle.com/collection/ai
    • https://teachablemachine.withgoogle.com/
    • https://quickdraw.withgoogle.com/
    • https://magenta.tensorflow.org/assets/sketchrnndemo/index.html
    • https://pair-code.github.io/what-if-tool/uci.html
  • Materials for AI outreach for general public

    • https://www.coursera.org/learn/ai-for-everyone/lecture/9n83j/more-examples-of-what-machine-learning-can-and-cannot-do​
    • https://teachablemachine.withgoogle.com/
    • https://playground.tensorflow.org
    • http://projector.tensorflow.org/
  • Explaining privacy preserving analysis to the public using a comic

    • https://federated.withgoogle.com/
  • Better images of AI

https://betterimagesofai.org/images

  • Ethics in mathematics (comics)

https://ethics.maths.cam.ac.uk/course/comics/

  • AI for companies

    • https://landing.ai/resources/ai-transformation-playbook/
  • Resources for training and teaching data scientists

https://github.com/neelsoumya/readinglistjournal_club

  • Working with domain experts

https://github.com/neelsoumya/workingwithdomain_experts

Code

https://github.com/googlecreativelab/teachable-machine-v1

Requirements

A laptop/desktop/smartphone with an internet connection.

Manuscript and citation

If you like or use this work, please cite the following manuscript:

Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies Soumya Banerjee, Phil Alsop, Linda Jones, Rudolf Cardinal, Patterns 3(6), 2022

https://doi.org/10.1016/j.patter.2022.100506

Support and contact

  • Soumya Banerjee

  • sb2333@cam.ac.uk

If you like like or use this, please cite the following DOI:

https://doi.org/10.1016/j.patter.2022.100506

and the following manuscript

Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies Soumya Banerjee, Phil Alsop, Linda Jones, Rudolf Cardinal, Patterns 3(6), 2022

https://doi.org/10.1016/j.patter.2022.100506

Owner

  • Name: Soumya Banerjee
  • Login: neelsoumya
  • Kind: user
  • Location: Cambridge, UK
  • Company: University of Cambridge

My research interests are in complex systems data science, machine learning, computational biology, computational immunology and computational immunogenomics.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below: Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies, Soumya Banerjee, Phil Alsop, Linda Jones, Rudolf Cardinal, Patterns 3(6), 2022"
authors:
- family-names: "Banerjee"
  given-names: "Soumya"
  orcid: "https://orcid.org/0000-0001-7748-9885"
- family-names: "Alsop"
  given-names: "Phil"
- family-names: "Jones"
  given-names: "Linda"
- family-names: "Cardinal"
  given-names: "Rudolf"
title: "Patient and public involvement to build trust in artificial intelligence: a framework, tools and case studies"
version: 1.0.0
doi: 10.1016/j.patter.2022.100506
date-released: 2022-06-06
url: "https://github.com/neelsoumya/outreach_ppi"

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Dependencies

DESCRIPTION cran
  • bookdown * imports
  • ggplot2 * imports
  • knitr * imports
  • rmarkdown * imports
  • shiny * imports
  • sqldf * imports
  • tinytex * imports