Expert: data scientists need to focus more on healthcare sector

Specific strengths of AI, says one platform developer, can be a very good match in filling in some of human nature's organic gaps and, by extension, helping doctors provide safer, more thorough treatment to their patients.
Jeff Rowe

It seems safe to say today's artificial intelligence capabilities have advanced exponentially over the past decade due to breakthroughs in computing technology and the use of the cloud.  As a result, AI is leading to the much broader practice of machine learning and deep learning across the economy.  

But according to some observers, healthcare’s use of AI is lagging. One such observer is Veerachat Petpisit, CEO of Healthcare Venture, Bridgeasia, an AI development services provider.

As he sees it, the best days of AI in healthcare have barely begun.  One problem, he says, is that “the technology is still in the hands of data scientists, computer experts and machine learning enthusiasts. Promising uses in another setting or country are labelled as ‘science fiction’ or ‘too good to be true’ by most clinical practitioners. (And) patients are still very skeptical.”

Indeed, in his view, “the knowledge gap to artificial intelligence in healthcare is so huge that it creates fear of uncertainty with even the slightest thought of introducing artificial intelligence in the clinic. It would be no different from the reaction of a hunter-gatherer living in a shack being told that someone is going to bring fire into his house for warmth and light. The fundamental complexity of machine learning does not go along well with the very busy nature of healthcare practitioners in the effort to understand and fully utilize the technology. On the other hand, practitioners who fall in love with machine learning, having clinical data and the vision to create a system that can solve pressing healthcare issues, end up developing the system themselves and leaving their practice behind.”

What is needed, he argues, is data scientists who understand healthcare enough to be able to appreciate the value of AI in specific case contexts and determine what data is needed for creation.

“Software engineers who create systems that house the artificial intelligence systems must be able to master the workflows and processes to come up with systems that can integrate the new technology with existing methods of practice. We need to produce more of these scarce talents so we can experiment and implement more innovative ideas, hoping that some will mature and help solve the numerous healthcare issues we constantly encounter.”