This article by Morris Panner, CEO, Ambra Health was originally posted on ai-med.io on July 20, 2018.
We share a lot of pictures – our family, our friends, our pets, and even our food. Sharing photos has become seamless and the face recognition feature offered by Facebook has put powerful algorithms in the hands of millions for free.
However, accessing and sharing medical images, a critical piece in the healthcare puzzle, often remains stuck in the world of CDs and fax machines.
Leading healthcare providers across the globe place a constant focus on innovation around all aspects of the care continuum. Medical imaging is no exception, particularly when grappling with growing data volume, patient consumerism and shifting trends of care models.
At radiology conferences like the RSNA annual meeting in Chicago, AI was by far the most talked about trend for 2018.
Many practitioners are excited about its potential to transform everyday workflows and there are many potential use cases, for example using algorithms to automatically align current and prior exams for instant comparison of multiple studies.
We know that AI could prove highly beneficial for radiologists by cutting down on read times and improving accuracy. In addition, AI could be a strong resource for mining large data sets for both individual patient care and global insights. But first, we must access the images.
A cloud-based repository makes possible the type of large scale data analysis and analytics that are enabling innovations large and small across other areas of the economy
Today’s traditional hardware, CDs, and PACS (picture archiving communications system) lock data deep inside them and prevent interoperability.
We have seen the cloud act as a key technological innovation for the storage of large imaging sets and easy access to patient priors through automated matching.
Modern cloud-based APIs can integrate with upstream and downstream systems like portals for patient self-service, or into EMRs/EHRs to improve physician productivity and access. A cloud-based viewer also allows image access from anytime and anywhere.
In the clinical trial world with the cloud, eliminating physical media can improve the percentage of submission-compliant images automatically, reduce errors, and provide a secure archive. A cloud-based repository makes possible the type of large scale data analysis and analytics that are enabling innovations large and small across other areas of the economy.
Today, there are amazing outcomes that machine learning and artificial intelligence could offer patient care by integrating and analyzing complex data sets. The goal is not to remove the physician from the process, but rather provide them with easy access to the imaging data and aid them in making the best decision possible for a patient.