How Machine Learning Is Driving Better Patient and Business Outcomes

The last few years have seen great advances in healthcare and lifesciences technology, with some of the biggest breakthroughs driven by machine learning and artificial intelligence (AI). Machine learning, AI, and other intelligent technologies are powering devices and software applications that allow us to accelerate drug discovery, development, and approval; create personalized patient treatment plans that lead to healthier outcomes; diagnose diseases and abnormalities earlier and more accurately; and build more efficient infrastructure for healthcare and life sciences organizations. The healthcare industry is aggressively investing in intelligence: Tractica, a leading market research firm, projects that spending on healthcare AI technology will surpass $34 billion by 2025, compared to $2.1 billion in 20181. And according to Accenture, those investments will pay off, with the top AI healthcare applications predicted to create $150 billion in annual savings by 20262.

That’s not to say the relationship between healthcare and life sciences and technology is perfect, however. The industry is struggling to adopt innovation quickly and meaningfully, and many providers are frustrated by systems that actually hamper their productivity with electronic health record (EHR) systems often taking the brunt of the blame. But machine learning is far from “just another technology in the stack.” It has the power to overcome healthcare and life sciences challenges by providing a platform for operational and clinical efficiency, driving costs down, and improving patient care.