There are many moving parts and there is a lot of information passing before our eyes. This is my version of a summary snapshot as we move into Summer 2018. What did I forget? Please add your thoughts below.

6 quick tips, links and areas to consider as we move forward.

1. Pay attention to Drs. Dreyer and Michalski and their team at MGH & BWH CENTER FOR CLINICAL DATA SCIENCE

“Radiologists will not be replaced by ML, however radiologist who don’t use ML may be replaced by those who do.” Mark Michalski and Keith Dreyer

2. Get a sense of what’s out there.

There were 30 ML/AI companies at RSNA last year and Dr. Harvey has done a nice job curating the list:

The A-Z Guide to Radiology AI Companies

Per MIT, there are 130 companies working on AI and healthcare in China

3. See where the ML vendors are working to add to our current workflow. Some examples: Carestream, Fuji and IBM.


Fujifilm Showcases Enterprise Imaging Portfolio and AI Initiative

TriHealth hospitals pay $10 million to adopt IBM Watson Health enterprise imaging

4. Take an intro ML class online – for free.



Get a sense of how computer scientists think. We are not so different but there are clinical things that they just don’t know. And that brings us to:

5. Own this paradigm shift.

Once we have an idea of how developers think, we can offer helpful feedback.

“I love my EMR” said no one ever. Let’s be involved in this tech shift. When your institution adopts an algorithm, insist on a system to provide user feedback.

There are so many areas to improve within radiology and between radiology and our clinical counterparts. Be creative. Think big.

6. Subscribe to a few newsletters with AI and ML stories, healthcare and others:



We are at the very beginning of this new time in radiology and quite frankly you could probably navigate the rest of your career and avoid any significant change.

But where is the fun in that?