Changing the game in Cancer … through Advanced Data Science
"Automating tumor progression measurement: a sweet spot for artificial intelligence"
Assessing change in tumors is an important part of the clinical evaluation of cancer but current practices rely on human observations that are time consuming and can vary. Artificial Intelligence (AI) and machine-learning are well positioned to improve efficiency and accuracy of tumor assessment. This innovation will have a significant impact on the speed, cost, and accuracy of cancer clinical trials. What are the challenges to delivering this solution?
- Lawrence H. Schwartz, MD, Chairman, Department of Radiology, Columbia University Medical Center and Co-Chair of Project Data Sphere Images & Algorithms Task Force
- Craig Tendler, MD, Vice President, Clinical Development & Global Medical Affairs, Oncology, Janssen Pharmaceutical Company of Johnson & Johnson