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Virtual Hackathon &

In-Person Co-Working & Demo Day in San Francisco

Purpose

Welcome to Stanford Medicine and Research to the People's Rare Disease AI Hackathon. The purpose of this event series is to bring AI and medical experts together to build open source language models for rare diseases, and create zero-barrier access to rare disease expertise for patients, researchers and physicians. We're excited for the potential AI has to uncover novel links between rare diseases. As models are built and tested, we will also explore validation methods for medical AI models. Our team is excited to jumpstart an open source community for rare disease AI models. Successful models will be released for further testing and validation on Hypophosphatasia.ai and EhlersDanlos.ai.

Timeline 

Note: Exact dates are still being finalized.

  • Janurary 2024 Event Announced and datasets released.

  • Month/Date/Year: Kick-off event. Teams work on models. Office hours sessions on training, fine tuning and validating models. Virtual and In-person.

  • Month/Date/Year: In-person co-working and office hours hosted by Fifty Years

  • Month/Date/Year: In-person co-working and office hours hosted at TBD. 

  • June 2024: In-Person Demo Day! Open to the public.

  • Ongoing: Models released for Beta testing to broader patient and physician community by Research to the People. Teams will be invited to publish their work in the Research to the People Journal.

 

Rare Disease Focus

  1. Hypophosphatasia.

  2. Ehlers Danlos Syndrome.

 

​Dataset

Clinical Guidelines and the entirety of PubMed publications for HPP and EDS. Additional novel data is expected to become available. Downloads coming soon.

  1. Hypophosphatasia [Preprocessed Graph Format] [Raw Data]

  2. Ehlers Danlos Syndrome [Preprocessed Graph Format] [Raw Data]

Problem

  1. Create custom models for Hypophosphatasia and Ehlers Danlos Syndrome.

  2. Advanced: Interface the models to create novel research connections between HPP and EDS.

Hackathon Events

The bulk of this hackathon will take place virtually, with teams interfacing with AI Researchers, Patients, and Medical experts through in-person (SF Bay Area) and virtual sessions. This hackathon will focus on:

  1. Fine tune training.

  2. Doctors, Patients and Medical Experts interrogating models.

  3. Advanced: Developing methods for models to interface with each other, creating the possibility of new research links between HPP and EDS.

 

Format

We're doing a rolling start, and welcoming teams to start building models ASAP. Teams can signup and access the data right away to start training their models. Virtual and in-person hackathon events and office hours will be hosted by our team and leading experts leading up to the demo day in June 2024.

 

Over the course of these events, teams will focus on fine-tuning models with AI and medical experts. This work will culminate in a live demo day pitch session with patients, medical experts, investors and the broader AI and Rare Disease Community. ​

Demo Day

Public Demo Day will be open to the broader AI and Rare Disease Community. Teams will present live demos of their models and lead a discussion on their approach. This event will feature VC's and investors who are funding generative AI in healthcare and medicine.​ Note: Models developed for the Hackathon are expected to be open-source. Teams will be able to connect with VC's and Investors for other generative AI projects.

Recommended Tools

  1. Llama 2

  2. Run Llama locally with GG.ML

  3. HuggingFace

  4. LangChain

  5. ChromaDB

  6. Pinecone

  7. Ray

Recommended Reading

  1. The shaky foundations of large language models and foundation models for electronic health records.

  2. Challenges and Applications of Large Language Models.

  3. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers

Purpose

Bring AI and medical experts together to build open source models for rare diseases. Create zero-barrier access to rare disease expertise for patients, researchers and physicians. Use AI to Uncover novel links between rare diseases. Establish validation methods for medical AI models. Jumpstart an open source community for rare disease AI models. Launch models for Beta testing on Hypophosphatasia.ai and EhlersDanlos.ai.

Timeline

  • August 2023: Hackathon and Demo Day announced.

  • September 2023: Datasets released.

  • October - January 2023: Teams work on models. Office Hours and Hackathon Events to train tune and validate models hosted throughout.

  • February 2024: Demo Day. Event open to the public.

  • Post Hackathon: Models released for Beta testing to broader patient and physician community by Research to the People. Any joint publication efforts will be led by Research to the People.

 

Rare Disease Focus

  1. Hypophosphatasia.

  2. Ehlers Danlos Syndrome.

 

Dataset

Clinical Guidelines and the entirety of PubMed publications for HPP and EDS:

  1. Hypophosphatasia - Download coming soon. [Preprocessed Graph Format] [Raw Data]

  2. Ehlers Danlos Syndrome - Download coming soon. [Preprocessed Graph Format] [Raw Data]

 -- The availability of additional genotypic and phenotypic datasets are currently being evaluated. --

Problem

  1. Create a custom model for Both Hypophosphatasia and Ehlers Danlos Syndrome.

  2. Advanced: Interface the models to create novel research connections between HPP and EDS.

Hackathon Events

The bulk of this hackathon will take place virtually, with teams interfaceing with AI Researchers, Patients, and Medical experts through periodic in-person (San Francisco) and virtual sessions. we will The hackathon will focus on:

  1. Fine tune training.

  2. Doctors, Patients and Medical Experts interrogating the models.

  3. Advanced: Developing methods for models to interface with each other, creating the possibility of new research links between HPP and EDS.

 

Format

We're doing a rolling start, and welcoming teams to join before December 2023. Teams can signup and access the data right away to start training their models. Virtual and in-person hackathon events and office hours will be hosted by our team and leading experts leading up to the demo day in February 2024.

 

Over the course of these events, teams will focus on fine-tuning models with AI and medical experts. This work will culminate in a live demo day pitch session with patients, medical experts, investors and the broader AI and Rare Disease Community. ​

Demo Day

Public Demo Day will be open to the broader AI and Rare Disease Community. Teams will present live demos of their models and lead a discussion on their approach. This event will feature VC's and investors who are funding generative AI in healthcare and medicine.​

 

Note: Models developed for the Hackathon are expected to be open-source. Teams will be able to connect with VC's and Investors for other generative AI projects.

Recommended Tools

  1. Llama 2 

  2. Run Llama locally with GG.ML

  3. HuggingFace

  4. LangChain

  5. ChromaDB

  6. Pinecone

  7. Ray

Recommended Reading

  1. The shaky foundations of large language models and foundation models for electronic health records.

  2. Challenges and Applications of Large Language Models.

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Organizers

Pete Kane

Stanford Medicine & Founder of Research to the People.

Stanley Bishop

Founder, Foundation.Science

Ex Google.

Chloe Hsu, PhD

Machine Learning Scientist.

Ex: Google, Meta,

UC Berkeley, Cal Tech Alum.

Jacob Cole

Founder, IdeaFlow.

MIT Alum.

Majo Durán

Bio Fellow at Fifty Years.

USCF Immunotherapy Scientist.

Patient Collaborators

Gigi

Hypophosphatasia & Ehlers Danlos Syndrome Patient. Grant Writer & RTTP Collaborator.

John

Patient Advisor. Founder, BioHackers Guild. 

Undiagnosed-1 Patient.

Sue

Hypophosphatasia Patient Collaborator.

Sam

Citizen Scientist and Systems Biologist Patient-Turned-Researcher.

More Coming

Medical & AI Experts

Michael Snyder, PhD

Chair, Stanford Medicine, Genetics and Personalized Medicine.

Lara Bloom

President & CEO of The Ehlers-Danlos Society.

Fanny Sie

Head of AI and Emerging Technology External Collaboration (M&A, Partnering), Roche Global Informatics

Katie Link

Machine Learning Engineer at Hugging Face, ML Research Engineer at NYU Langone Health.

Dr. Woody Gandy

Internal Medicine, Board of Directors, Ehlers-Danlos Society.

Bharath Ramsundar, PhD

Founder, Deep Forest and Deep Chem. O’Reilly Author. UC Berkeley & Stanford Alum.

David Hall, PhD

Research Engineering Lead at
Stanford HAI. Ex. Microsoft. UC Berkeley & Stanford Alum.

Avantika Lal, PhD

Principal AI Scientist at Genentech (Roche)

Ex. Insitro, NVIDIA Research. Stanford Alum.

More Coming

Check us out on OpenChallenges.io

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