Where Does the Medical Record Fit into Integrating AI?

June 7, 2019

In the fifth episode in our AI Conversation video series, join TeraRecon President and CEO, Jeff Sorenson as he examines how AI and medical records will work together in the future to provide better patient care and understanding of disease progression.

How AI Will Work Together With Patient Records to Improve Patient Care

The medical record certainly has a very strong place in AI. While TeraRecon’s main focus is imaging and imaging informatics, there is a lot of data that can help identify when there might be findings in the patient’s imaging. There is also AI that can find markers in the images that lets you go back and interrogate the patient’s medical record. What the physician really wants is both of those things side by side and interactive. So if they see something in the medical record, they want to be able to search the images for those types of findings and similarly, if we can identify things in imaging before they are ever even read, then our systems can go and search the medical record. When the radiologist reads it, all of the relevant patient history is right there in front of them at the same time that they are reviewing the current study, and any findings in the current study that are also found in prior studies can be marked.

When we talk about precision imaging, imagine that today radiologists don’t have time to measure every single finding so they start generalizing and saying “approximately” or “I’ve appreciated something” but they are not measuring 5mm. Now if the computers can do that automatically, then the computer can say “here it is, it is 5mm and the prior is 3 mm.” This is really important for the patient because much of our care is determined by what the progression of the disease is. So, if in the prior report, we haven’t really measured that anatomy, then in your subsequent scan you also can’t precisely tell that kind of doubling time. It takes too much work to go back in time and reconstruct everything. So better precision on the front end is going to mean better care for serial studies.

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