Improving cloud computing, machine learning with Google

Google has introduced a suite of new partnerships utilizing the power of cloud computing and machine learning to advance the field of diagnostic imaging. Presentations were given at the annual meeting of the Radiological Society of North America (RSNA) in Chicago.

Artificial intelligence and cloud computing are continually advancing and assisting in improving care. In the presentation, Google Cloud was the center of attention and outlined its mission to organize the world's health and life science information to make it accessible, secure and useful. To achieve this goal, Google is changing the way research and medicine are performed by bringing individuals to the data.

Google presented along with a variety of partners who have utilized Google Cloud computing and machine learning to improve diagnostic imaging. These partners included:

Dicom Systems — Awarded best-in-class Enterprise Imaging workflow and interoperability solution for healthcare provides, Dicom Systems is responsible for the flow of over 8 billion images per year. In achieving integration of electronic medical records with systems like Epic and Cerner, Dicom is working with Google to securely handle and share massive amounts of data. 

“Our interest with Google is not strictly to provide a cloud, it is to contribute to the identification of data into a data link,” said Florent Saint-Clair, the Executive Vice President of Dicom Systems. “That data link is provided to researchers around the world in order to perform their machine learning algorithm training.”

Ambra — Another imaging workflow solution, Ambra plans to use Google Cloud technology to cut costs and improve interoperability. In their solution overview, Ambra outlines how the stages of storage & achieve, access & exchange, interoperability and value allow for the customization of the kind of workflow system required.

Life Image — Life Image’s presentation focused on how using multi-source clinical data during cancer screenings could improve screening rates, expand referral networks, accelerate outreach programs and push collaborations forward. Within the Life Image workflow system presented, healthcare professionals are able to search by characteristics for patients similar to the one they are treating for improved research.

Imagia — Imagia aims to use the power of AI to advance the space of precision medicine through an integrated evidence clinical ecosystem. The company showcased their leveled clinical data system for the scaling up of radiomic discovery, utilizing machine learning and AI to analyze samples of data and identify anomalies.

“Together, Google and Imagia really facilitate the clinical validations of radiomic research with the intent to ensure the expertise, time and energy is contributed where we would have the most impact in terms of patient management and beneficial care,” said Imagia Chief Technology Officer, Florent Chandelier.