Bridging IT and medical knowledge to advance healthcare AI
With an expected gradual increase in demand for innovative healthcare solutions, technology providers have flooded the market with various AI solutions. They are all trying to take a piece of the market that could potentially be valuable $188 billion by 2030.
The largest investors, healthcare providers, have realigned their budgets around AI to primarily increase their competitiveness and reputation and in turn maintain the trust of their patients.
However, most AI implementations in healthcare remain stuck in the research phase.
“About half of the projects go from pilot to production,” said Ho-Young Lee, professor and director of Research and Development at Seoul National University Bundang Hospital.
The reason for this lies in the collaboration between clinical and IT teams.
“In my personal experience, if we somehow collaborate with another specialized field (such as IT), it takes at least three years for doctors to understand their terms… and for the IT engineering (team) to understand the medical terms, ” shared Prof Lee.
“To develop and maintain AI services that can be used continuously in the medical field, it is important that a group of experts and technologically advanced companies work together,” he said during the session.Healthcare AI open innovation in SNUBH.”
SNUBH has demonstrated such multidisciplinary collaboration in the various AI open innovation projects in which it is currently involved.
Nationally, it is part of 30 hospitals working with approximately 400 healthcare professionals and 19 tech startups to develop AI solutions targeting 12 common chronic and acute diseases. The government-backed Dr. Answer 2.0 project is now in its third year and is working to gain local regulatory approval for 24 solutions.
SNUBH also has ties with GE Healthcare to support local medical startups in accelerating the development and implementation of their respective solutions by leveraging the Edison platform.
For these partnerships to thrive, it is critical that both medical and IT teams can communicate and understand each other’s language.
“We need a specialist who can understand both languages and help translate and share their ideas,” Prof. Lee suggested. “The way an IT engineer thinks is different from the way a doctor thinks.”
“But if we do not understand each other, we will not succeed in developing AI solutions,” he emphasized.