With breakthroughs coming out almost on a daily basis, the impact of artificial intelligence (AI) on healthcare is nothing less than profound. Here on the APEX of Innovation, we’ve covered how AI improves healthcare outcomes and saves lives, including carrying out digital consultations and helping better identify cancers and tumors with predictive analytics. Telemedicine is also becoming a reality thanks to AI. As reported by ZDNet, doctors in India recently performed the world’s first long-distance surgery using a robot.
The proliferation of AI into hospitals and doctor’s offices across the globe is changing the face of patient care—and there’s no end in sight. In fact, the global market for AI in healthcare is expected to rise from $1.3 billion in 2019 to $10 billion by 2024, according to investment bank Morgan Stanley.
But when is AI right for treatment versus the ‘human touch’ of a living and breathing doctor or nurse?
According to a recent CNN Health article, while AI is not quite up to the level of human doctors, it’s catching up fast. Researchers at the University Hospitals Birmingham NHS Foundation Trust in the United Kingdom recently examined how deep learning, in particular, can identify patterns of disease by examining thousands of images and use those patterns to improve a future patient’s diagnosis. Using data from 14 different studies, the researchers found that deep learning algorithms correctly detected disease in 87 percent of cases, compared to 86 percent for healthcare professionals. According to the article, AI was also able to correctly identify those patients free from disease in 93 percent of cases, compared to 91 percent for healthcare professionals.
While the study showed AI adoption and success in healthcare are on the rise, the UK-based researchers stressed the need for more research, especially research that is conducted in a more realistic setting akin to what doctors face every day.
In the meantime, we’ll keep an eye for more innovative AI use cases in healthcare, including this one from TIBCO customer University of Iowa Hospitals, which reduced surgical infections by 74% with predictive analytics.