BOSTON, November 23, 2021 (GLOBE NEWSWIRE) – Rhino health today announced a pilot project with the National Cancer Institute’s Pancreatic Cancer Working Group Early Detection Research Network (EDRN), focused on interagency collaboration to improve outcomes for people who have been diagnosed or are at risk of developing pancreatic cancer. By using federated learning, participating institutions hope to recruit more collaborators and accelerate the execution of large-scale research without the clutter caused by the current need to share data.
Investigators will use multimodal data – including CT scans, motion pictures, and lab test results – to create AI models that speed up the diagnosis of pancreatic ductal adenocarcinoma (PDAC). When PDAC is diagnosed earlier, the likelihood of survival is considerably higher. The researchers hope to allow an earlier diagnosis and the adaptation of a more precise treatment. Participating institutions include Johns Hopkins Medicine, MD Anderson Cancer Center, Dana-Farber Cancer Institute, University of Pittsburgh Medical Center, Cedars-Sinai Medical Center, and City of Hope National Medical Center.
“One of the biggest challenges in pancreatic research is accessing the large datasets needed to draw scientific conclusions,” said Elliot Fishman, MD, professor of radiology, surgery, oncology and urology. at Johns Hopkins Hospital. “No institution can do it alone. Interagency collaboration is key to changing the trajectory of pancreatic cancer patients, and federated learning allows multiple researchers to use relevant data while still protecting confidentiality and without creating additional administrative or IT burden. “
With federated learning, AI models are trained using data from disparate sources with no sharing or aggregation of data. This protects privacy, makes it easier to access more diverse datasets, and makes it easier for medical researchers and AI developers around the world to collaborate. Rhino Health is an NVIDIA partner and member of the Creation of NVIDIA program. Rhino Health leverages NVIDIA’s federated learning technology in the Rhino Health platform, an end-to-end federated learning solution that allows researchers to quickly set up a project and easily add collaborators.
“Rhino Health puts the power of federated learning into the hands of leading medical researchers, leveraging the advanced capabilities made possible by NVIDIA’s federated learning technology,” said Mona Flores, MD, head of medical AI at NVIDIA. “This platform approach is well aligned with our vision for the future of federated learning, which we believe will fundamentally change the way AI for healthcare is developed and deployed. ”
“To realize the transformative promise of healthcare AI in the early detection of pancreatic cancer – and more broadly in radiology practice – we must collectively adopt common standards and principles in the management and use of data, ”said Eugene Koay, MD, PhD, Associate Professor, Department of Gastrointestinal Radiation Oncology at MD Anderson Cancer Center. “Together, medical researchers and industry are doing it, and federated learning helps ensure that we keep observations in context, maintain high-quality data, and collaborate in a very transparent manner in the service of patients. patients. “
The EDRN, supported by the National Cancer Institute (NCI), is a consortium of more than 300 researchers from academic institutions and the private sector working to discover, develop and validate biomarkers and imaging methods to detect cancers at an early stage. The consortium is also working to assess the risk of developing cancer and translate biomarkers and imaging methods into clinical trials.
“Transforming research findings into clinical practice requires assurance that an AI model will function consistently among today’s increasingly diverse real-world patient populations,” said Michael Rosenthal, MD, PhD, Assistant Professor of Radiology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, and Harvard Medical School. “This means that we need to use diverse datasets from the early stages of research, and federated learning is essential to provide globally relevant generalizable methods to detect pancreatic cancer earlier.”
Several of the principal investigators of this pilot project will present their work and the envisaged collaboration with Rhino Health during a virtual industry presentation at the next annual meeting of the Radiological Society of North America (RSNA). The session will take place online on Tuesday, November 30, from 12:15 to 3:15 p.m. CST, titled “Accelerating AI: How Federated Learning Can Protect Privacy, Facilitate Collaboration, and Improve Results.”
“We are touched by the ingenuity and dedication of these leading physicians and scientists, who are revolutionizing clinical medicine using AI,” said Ittai Dayan, MD, Co-Founder and CEO of Rhino Health . “For that, they must be able to collaborate effectively and efficiently, using a common platform and without the risk of invading patient privacy. We hope that Rhino Health’s “Federated Learning as a Platform” solution will be a useful tool at their disposal to help accelerate the impact of AI in healthcare. “
About Rhino Health
The Rhino health The platform enables medical researchers and healthcare AI developers to seamlessly access diverse and disparate data sets and use them to build better AI algorithms. Built on federated learning, Rhino Health enables collaboration without ever moving data, transferring ownership, or risking patient privacy. Based in Boston, MA, Rhino Health is a growing team of healthcare, AI and technology experts committed to accelerating the creation and adoption of AI-powered health solutions for patient populations. increasingly diverse.
Image 1: Rhino Health logo
Rhino Health provides federated learning for healthcare AI.
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