Radiologists are probably the techiest and they are proud of it. “They foresee a future like Star Trek where all we have is a machine and those working around the machine are radiologists,” Arielle Shoham, vice-president of marketing at Aidoc, told AIMed at the recent European Congress of Radiology (ECR) 2019. 

Indeed, with a press release which addresses artificial intelligence (AI) in its opening, an exhibition hall (AIX) and theatre set up to showcase only radiological AI and a free juice bar named “algorithm”. ECR 2019 is trying to realize its bigger picture which involves technology. This is not the first time an annual event like this makes room for AI. Two years ago, at the Radiological Society of North America (RSNA), attendees also witnessed a similar AI bandwagon like never before. 

Last summer, Signify Research published a report to forecast AI in medical imaging to reach $2 billion by 20203. All these show that even if not all radiologists dream of Star Trek, some of them are creating it right now. But the question is: how do we translate such enthusiasm to other facets of medicine? 

Concerns Removal and convergence of expertise 

Shoham believes in general, the medical field does not fear AI. This is evident in all the advanced tools that already existed. However, there remains a concern; the worry that one day human is going to be replaced. “I think radiologists are not going to be replaced because these are human facing positions. Technology is here, so that patients have more consultation time and you have more time to treat them, to do the things that you do,” Shoham said. 

On the other hand, Michele Debain, senior director for business development at iCAD notes that even within radiology, AI adoption is concentrated in lung, breast and brain imageries. These are, perhaps, the more researched areas, which give clinicians more facts to work on. Likewise, for most radiological AI companies, they tend to begin their venture in respective niche markets, areas which they know they can excel in. As such, Debain feels only when separate ideas and expertise start to converge and our knowledge of different organs come together, we may be able to capture a bigger wave of change in healthcare. One which enables AI to exercise its influence on different areas. 

Joren Reynders, lead solution architect and data protection officer of M*Modal added, because every specialty of medicine is different, so healthcare professionals may be looking at the same pool of documents from different angles and sources. Thus, real time feedback on the way clinicians record their work, is crucial to create some form of standardization, to bring everyone to the same translation point. 

Trust back by evidence and results 

Others like Maud Ménard, marketing manager of Aidance sees the importance of debunking hypes around AI and shows that it works in reality. She said, “I think once all the doctors and those within hospitals see AI can actually bring values, people will be ready to pay for it. In a way, it will also create more trusts”.

“I think results are the best way to demonstrate something is working. There is a couple of audiences you need to get excited about this technology,” Julie Sufana, chief marketing officer of ContextFlow asserted. She said most healthcare professionals enter the industry with the goal of providing help. Hence, they will be totally on board as long as they are convinced that a new tool will allow them to render better help. 

But then, as Sufana continued, it is also essential to include the patients themselves. Primarily, she believes in educating the public and showing them, what AI can achieve. “I think it is a kind of pull and push. Patients can push doctors to adopt more and in a faster manner, if they are excited about what AI can do”.


Author Bio

Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.