AI for Immunology:

A Resource Hub of AI Tools for the Immunology Community

Learning Resources

Although the most cutting-edge research is published in premier academic journals, announcements for AI tools are found in a host of other places online. In most cases, notices about new AI tools aren’t usually written up in research papers, nor are they peer-reviewed.

Instead, the latest news can be found on social media platforms, community forums, professional networking sites, personal blogs, and technology media sites. We plan to update this list of resources over time, and if you have suggestions of materials to share, please let us know and we would be happy to add to the list.

Table of contents

  1. Learning Resources
  2. Staying Up-to-Date
    1. Latest Scientific Articles
    2. Social Media
    3. Professional Networking Sites
    4. Community Forums
    5. Blogging and Tutorial Sites
    6. Scientific Workshops and Conferences
    7. Books for Emerging Tech Trends
    8. Technology News Digests
    9. General Media Coverage
  3. Formal Schooling vs. Self-Taught Methods
    1. Bioinformatics
    2. Immunology
    3. Data Science Skills
    4. Precision Health
  4. Massive Open Online Courses (MOOC)
    1. Prompt Engineering Course for ChatGPT
    2. ChatGPT Prompt Engineering for Developers
    3. Stable Diffusion
  5. Machine Learning Operations
  6. AI4Science Community

Staying Up-to-Date

Latest Scientific Articles

  • bioRxiv (preprint server)
  • arXiv (preprint server)

Social Media

  • Twitter/X
  • Instagram
  • TikTok
  • Facebook
  • YouTube

Professional Networking Sites

  • LinkedIn

Community Forums

  • Reddit
    • r/ChatGPT
    • r/ChatGPTCoding
    • r/OpenAI
    • r/MachineLearning
    • r/cscareerquestions
    • r/datascience

Blogging and Tutorial Sites

  • Medium
  • Substack
  • Towards Data Science

Scientific Workshops and Conferences

  • Machine Learning for Health (ML4H) Symposium
  • Conference on Health Learning Inference (CHIL)
  • NeurIPS and Related Workshops
  • ICML and Related Workshops
  • SC (Supercomputing) Conference
  • UMich Workshop
  • GenAI for Oak Ridge Science Workshop
  • ISMB/ECCB Conferences
  • Stanford Future of Gen AI in Medicine Workshop
  • Open to more suggestions!
  • (May 2023) The AI Revolution in Medicine: GPT-4 and Beyond by Peter Lee, Carey Goldberg, and Isaac Kohane
  • (Mar 2023) Impromptu: Amplifying Our Humanity Through AI by Reid Hoffman
  • (Nov 2022) Power and Prediction: The Disruptive Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
  • (Jul 2022) Future Skills: The 20 Skills and Competencies Everyone Needs to Succeed in a Digital World by Bernard Marr
  • (Jun 2022) Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen
  • (Nov 2021) The Age of AI: And Our Human Future by Henry Kissinger, Eric Schmidt, and Daniel Huttenlocher
  • (Oct 2020) The Alignment Problem by Brian Christian
  • (Jul 2020) After the Digital Tornado: Networks, Algorithms, Humanity by Kevin Werbach
  • (Oct 2019) Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell
  • (Oct 2019) Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell
  • (Sept 2019) Rebooting AI: Building Artificial Intelligence We Can Trust by Gary Marcus and Ernest Davis
  • (Sept 2015) The Master Algorithm by Pedro Domingos
  • (Nov 2003) The Creative Mind: Myths and Mechanisms, 2nd Edition by Margaret Boden

Technology News Digests

  • Wired
  • TechCrunch
  • MIT Technology Review
  • Mashable
  • Engadget
  • StatNews
  • TechXplore
  • ZDNet
  • Artificial Intelligence News
  • Gizmodo
  • Digital Trends
  • Ars Technica
  • KDNuggets

General Media Coverage

  • Forbes
  • BusinessInsider
  • And many more

In addition to the websites listed above, here are some summary articles curated with AI news outlets.

Formal Schooling vs. Self-Taught Methods

In today’s ever-evolving landscape of knowledge, the traditional model of returning to school for new degrees in emerging domains may not always be feasible. Instead, the role of scientists is increasingly that of lifelong learners.

Bioinformatics

Immunology

Section currently in progress

Data Science Skills

Section currently in progress

Precision Health

  • (Aug 2023) Tutorial: Precision Health in the Age of LLMs by Hoifung Poon, Tristan Naumann, Sheng Zhang, Javier González Hernández from Microsoft Research
    • Features slides and an expansive list of resources:
      • Precision Health
      • LLMs for Precision Health: GPT-4 in Medicine, Biomedical LLMs, LLMs for Real-World Evidence, LLMs for Drug Discovery
      • Application Challenges: Bias, Hallucinations
      • Research Frontiers: Prompt Programming, Retrieval-Augmented Generation (RAG), Knowledge Distillation, Multi-Modal Learning, Causal Discovery

Massive Open Online Courses (MOOC)

Massive open online courses (MOOCs) have emerged as a powerful tool to facilitate this continuous learning journey. Over the past decade, MOOCs have witnessed a remarkable increase in quality, credibility, and popularity. Academic institutions and industry leaders have collaborated to offer MOOCs across a wide range of subjects, from coding to data science, prompt engineering for both beginners and seasoned developers, stable diffusion, and more.

Here are a handful of examples provided within this list from Forbes: “The 29 Best (And Free) ChatGPT And Generative AI Courses And Resources”

Prompt Engineering Course for ChatGPT

A Vanderbilt University course delivered through Coursera that acts as an introduction to writing useful and effective prompts for those with little to no technical skills.

ChatGPT Prompt Engineering for Developers

Taught by AI legend Andrew Ng and OpenAI’s Isa Fulford aimed at those who want to code applications using ChatGPT. It’s currently free for a limited time.

Stable Diffusion

A course provided by the University of Central Florida detailing beginner and advanced methods for this powerful AI image tool.

Machine Learning Operations

  • Chip Huyen, Computer Scientist and Tech Writer
    • Professional Website
    • MLOps Guide, which includes:
      • ML + Engineering Fundamentals
      • MLOps Overview, Intermediate, and Advanced Resources
      • MLOps Career
      • MLOps Case Studies
      • Bonus Materials

AI4Science Community

AI for Science is a growing community dedicated to AI-assisted scientific discovery across a wide range of domains (pictured below). This community has hosted several workshops at ICML and NeurIPS in addition to publishing a Nature paper on the role of AI in scientific discovery.

A4Science Fig

Alt Text: A flow chart figure of a circle of arrows running in a circle from the text “AI for science” to “Hypotheses” to “Experiments” to “Observations” with a broad list of application areas underneath (weather forecasting, battery design optimization, magnetic control of nuclear fusion reactors, planning chemical synthesis pathway, neural solvers of differential equations, hydropower station location planning, synthetic electronic health record generation, rare event selection in particle collisions, language modelling for biomedical sequences, high-throughput virtual screening, navigation in the hypothesis space, super-resolution 3D live-cell imaging, and symbolic regression) (Source: 2023 Nature)

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