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.