ROCHESTER, Minn. — Mayo Clinic today unveiled separate groundbreaking collaborations with Microsoft Research and with Cerebras Systems in the field of generative artificial intelligence (AI), designed to personalize patient care, significantly accelerate diagnostic time and improve accuracy.
Announced during the 43rd Annual J.P. Morgan Healthcare Conference, the projects focus on developing and testing foundation models customized for various applications, leveraging the power of multimodal radiology images and data (including CT scans and MRIs) with Microsoft Research and genomic sequencing data with Cerebras. The innovations have the potential to transform how clinicians approach diagnosis and treatment, ultimately leading to better patient outcomes.
Foundation AI models are large, pre-trained models capable of adapting to and carrying out many tasks with minimal extra training. They learn from massive datasets, acquiring general knowledge that can be used across diverse applications. This adaptability makes them efficient and versatile building blocks for numerous AI systems.
Mayo Clinic and Microsoft Research advance AI for chest X-rays
Mayo Clinic and Microsoft Research are collaboratively developing foundation models that integrate text and images. For this use case, Mayo and Microsoft Research are working together to explore the use of generative AI in radiology using Microsoft Research’s AI technology and Mayo Clinic’s X-ray data.
"Multimodal foundation models hold immense promise in tackling significant roadblocks across the radiology ecosystem. The innovations we’re creating with Microsoft Research will help unlock valuable insights for the future of medical imaging to improve how radiologists work and how patients are cared for," says Matthew Callstrom, M.D. Ph.D., chair of Mayo Clinic Radiology in the Midwest and medical director for Generative AI and Strategy. "Focusing on chest X-ray reports, Mayo's clinical teams and Microsoft researchers will collaborate to advance the state-of-the-art in multimodal AI radiology, helping bring innovation to real-world application faster and at scale, which is key to making exemplary healthcare more accessible."
Empowering clinicians with instant access to the information they need is at the heart of this research project. Mayo Clinic aims to develop a model that can automatically generate reports, evaluate tube and line placement in chest X-rays, and detect changes from prior images. This proof-of-concept model seeks to improve clinician workflow and patient care by providing a more efficient and comprehensive analysis of radiographic images.
"This collaboration is a crucial step towards our mutual goal of developing generative AI that improves patient outcomes and the clinician experience," says Jonathan Carlson, Ph.D., managing director, Health Futures at Microsoft Research. "The fusion of Microsoft's recognized research innovations in biomedical AI and Mayo Clinic's radiology excellence will empower clinicians with the tools they need to deliver more precise and accessible care and further Microsoft’s commitment to bringing the power of emerging AI to clinical researchers worldwide."
Mayo Clinic and Cerebras create a world-leading genomic foundation model
Mayo Clinic and Cerebras have created a genomic foundation model that combines publicly available human reference genome data that represents an ideal version of the human genome, with Mayo's comprehensive patient exome data and the power of its Mayo Clinic Platform. Exome data focuses on the protein-coding region of the genome where several disease-causing mutations take place. Cerebras's high-powered computing and generative AI capabilities make it possible to train and develop the model at scale, positioning it to be further refined for more specific uses.
"The genomic foundation model represents a significant advancement in personalized medicine," says Dr. Callstrom. "Its ability to analyze genomic data and compare them in almost real-time with patients with similar traits allows for more precise prediction of disease and treatment response, leading to faster diagnoses and the selection of targeted therapies for patients."
For example, rheumatoid arthritis (RA) is a debilitating autoimmune disease, and the standard treatment approach often requires trials of different therapies to achieve disease remission. It can take several months to know if a therapy is working. A new genomic model developed by Mayo Clinic and Cerebras offers a potential solution to shorten the time to identify effective treatment and avoid long-term morbidity associated with the untreated disease. Early findings demonstrate high performance against benchmarks and show early promise in identifying patient response to therapy. As more patient data is added, the model's predictive power is expected to increase, leading to faster, more effective personalized treatment for RA patients.
"Mayo’s genomic foundation model sets a new bar for genomic models, excelling not only in standard tasks like predicting functional and regulatory properties of DNA but also enabling discoveries of complex correlations between genetic variants and medical conditions," says Natalia Vassilieva, Field CTO at Cerebras Systems. "Unlike current approaches focused on single-variant associations, this model enables the discovery of connections where collections of variants contribute to a particular condition."
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