Announcing the launch of the Medical AI Research Center (MedARC)

We are proud to announce the launch of Medical AI Research Center (MedARC), a novel, open, and collaborative approach to research dedicated to advancing the field of AI applied to healthcare.

The progress of AI in other fields has had huge leaps, enabled by the training and utilization of large-scale models: GPT-3/ChatGPT has near-human performance at various text processing tasks, CLIP has enabled new multi-modal applications, and Stable Diffusion has provided efficient photorealistic text-to-image generation to the masses.

These large deep learning models, sometimes called foundation models, have enabled novel, previously inconceivable, applications. However, many of these advances have not had relevant use cases for medical AI for several reasons. This is because these models are domain-agnostic and not trained with medical data specifically, and therefore have limited medical knowledge and understanding.

We therefore believe that the research and development of large deep learning models specific to medical applications shows great promise.

Recently, we’ve seen very successful open-source, decentralized, initiatives result in impactful research in deep learning. For example, EleutherAI has developed the Pile dataset, one of the most-used datasets for training large language models, and released GPT-NeoX-20B, one of the largest publicly-available open-source large language models. OpenBioML has already replicated the results of AlphaFold and completely open-sourced their results, within only a few months of its existence.

We believe similar approaches will be beneficial for medical AI research. We establish an open and collaborative research community with access to computational resources and relevant expertise to pursue research on foundation models tailored to the medical domain.

While we place an important emphasis on the development of foundation models for medicine, we do not limit ourselves to this topic.

Successful medical AI research requires an interdisciplinary team of clinicians with a good understanding of medical problems as well as machine learning (ML) researchers and engineers who can apply the relevant state-of-the-art ML solutions or develop new solutions tailored to a specific clinical need.

For context, our team has worked on another initiative, WAMRI.ai which put together such interdisciplinary teams to tackle specific clinical problems over the period of several months at University of San Francisco. This initiative was quite successful, resulting in a few startups and publications, including a publication in Nature Methods.

MedARC is inspired by the success of WAMRI. Our collaborative and decentralized organization will bring together these disparate groups of experts and build such interdisciplinary teams to address various clinical needs with AI/ML solutions.

We are interested in having machine learning researchers, clinicians, academics, and others get involved in our mission to make a difference in healthcare with AI. We welcome people to join our current projects or also propose new collaborative research projects, which we can help accelerate with our large-scale compute resources!
MB Bureau