[Perspectives] Bridging the chasm between AI and clinical implementation

Many advances in artificial intelligence (AI) for health care using deep neural networks have been commercialised. But few AI tools have been implemented in health systems. Why has this chasm occurred? Transparency, suitability, and adaptability are key reasons. The deployment of any new technology is usually managed centrally in hospitals and health systems. For the information technology (IT) teams, there is the concern that input data are drawn from outside the health setting and the algorithm performance, source code, and input data are unavailable to review.

[Perspectives] Keith Wailoo: framing health challenges through a historical lens

While growing up in New York City, NY, USA, in the 1970s, Keith Wailoo could not avoid noticing giant billboard advertisements promoting menthol cigarettes. “I was surrounded by an aggressive promotion of menthol tobacco aimed at Black Americans in urban areas”, says Wailoo, the Henry Putnam University Professor of History and Public Affairs at Princeton University, NJ, USA. The saga of menthol tobacco is documented in Wailoo’s book Pushing Cool: Big Tobacco, Racial Marketing, and the Untold Story of the Menthol Cigarette.

[Perspectives] Bridging the chasm between AI and clinical implementation

Many advances in artificial intelligence (AI) for health care using deep neural networks have been commercialised. But few AI tools have been implemented in health systems. Why has this chasm occurred? Transparency, suitability, and adaptability are key reasons. The deployment of any new technology is usually managed centrally in hospitals and health systems. For the information technology (IT) teams, there is the concern that input data are drawn from outside the health setting and the algorithm performance, source code, and input data are unavailable to review.