Cleveland Clinic, IBM and the Hartree Centre collaborate to advance healthcare and life sciences solutions via artificial intelligence (AI) and quantum computing.
Cleveland Clinic, IBM and the Science and Technology Facilities Council’s (STFC) Hartree Centre have announced an innovative collaboration aimed at advancing healthcare and biomedical science through advanced computing technologies, including artificial intelligence (AI) and quantum computing.
“This partnership will play an important role in advancing research into the use of cutting-edge computation in healthcare and life sciences,” said Alessandro Curioni, IBM Fellow and Director, IBM Research Zurich.“We look forward to working with researchers from Cleveland Clinic London and the Hartree Centre to explore promising areas of discovery across quantum computing, AI and beyond.”
“This international collaboration brings together a multidisciplinary team of scientists, clinical researchers and physicians from across industry, government and healthcare,” said Lara Jehi, M.D., MHCDS, Chief Research Information Officer at Cleveland Clinic. “The research teams will leverage high performance and quantum computing to advance life sciences, with the goal of improving healthcare and accelerating new treatments for patients around the world. Cleveland Clinic London will be a central link between innovative clinical care in the UK and Cleveland Clinic’s global footprint.”
Two clinical research projects have been launched to kick-start the new collaboration. They will be led by Dr. Jehi, an epilepsy researcher, and Charles Knowles, Ph.D., Chief Academic Officer at Cleveland Clinic London, working closely with teams from IBM and Hartree Centre. The projects will be supported by the Hartree National Centre for Digital Innovation, a collaboration between IBM and Hartree Centre.
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Initially, the team will explore clinical and advanced imaging data provided by Cleveland Clinic London BioResource, a repository which provides patients with the opportunity to consent to enhanced longitudinal data collection and analysis.
The researchers plan to use this pilot study to develop larger AI models that can integrate multiple types of data for analysis across different diseases, ultimately aiming to improve understanding and patient care.
