Elsevier, a global information and analytics business specializing in science and health, has announced a new conference, AI and Big Data in Cancer: From Innovation to Impact. The conference seeks to bring together experts from all aspects of cancer research and the digital medicine value chain to understand how to translate artificial intelligence and data-driven innovations into new clinical care practices for patients. These leaders, including 2018 Nobel Laureate for Medicine, Dr. James Allison, will share pragmatic insights on finding the right partners to move innovations successfully forward.
According to Dr. Lynda Chin, Conference Chair, Founder and CEO of Apricity Health and Professor at Dell Medical School at the University of Texas, USA, the aim of this conference is to bring innovators together with stakeholders, from patients, clinicians and developers to regulators, payers and investors, so they can network and identify collaborators who can help them accelerate the translation of their innovation into clinical practices.
Leading voices from the US National Cancer Institute, DARPA, MIT, Harvard Business School, MD Anderson Cancer Center, Harvard, Columbia University Medical Center, Mayo Clinic, Broad Institute, J&J, Third Rock Ventures, PricewaterhouseCoopers, Friends of Cancer Research, Project Data Sphere, AI Global, Google Health, Amazon Web Services, among others will discuss and share insights on topics, including: Cultivating an AI and data literate generation; Building customer, business and regulatory trust; Generating rigorous evidence of clinical validity, health and economic benefits; Building infrastructure to enable integration, adoption and scale; and Advancing policies to promote innovation.
AI and Big Data in Cancer: From Innovation to Impact will convene on March 29-31, at The Westin Boston Waterfront. Interested parties may register by January 31, 2020, to save on conference fees.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.Click here to read the original press release.