Innovation Initiative to Develop Artificial Intelligence X-Ray Engine

The algorithm will be applied before X-Ray images are routed to one of the 500 board certified radiologists connected in the cloud to IA's platform.

“Inconsistency in testing and access to care contribute significantly to one trillion of waste in the USD 2.8 trillion U.S. healthcare industry,” said Brian Hall, President and COO of Imaging Advantage. “If successful, Singularity will introduce a solution with potential to transform radiology by providing faster, more accurate and less expensive diagnostic testing, representing an indispensable innovation for radiologists.”

“Given the advances in the field of artificial intelligence that have taken place at MIT and elsewhere, and Imaging Advantage's scale, we are not only optimistic about a successful outcome, but expect it to be realized on an accelerated schedule,” said Professor SP Kothari, PhD, of the MIT Sloan School of Management. “The project is not only achievable, but also has potential to touch nearly every person in world. This is how we think artificial intelligence and deep learning should be developed and deployed.”

“The proposed deep-learning solution combines all layers of machine learning into a single pipeline, and then optimizes and meshes with other machine-learning algorithms on top of it,” said electrical engineer Kalyan Veeramachaneni, PhD, of the MIT Institute for Data Systems and Society. “Starting this endeavor with the enormous trove of metadata in Imaging Advantage's archives, we can learn how decisions made at the initial, raw representation stage impact the final predicted accuracy efficacy.”

X-Ray exams constitute 50% of all radiology tests in healthcare, and radiology is the significant limiting factor in hospital emergency department (ED) patient flow and treatment.

Related Links:
Imaging Advantage
Massachusetts Institute of Technology
Massachusetts General Hospital