In 2020, few things went well and saw growth. Artificial intelligence was one of them, and healthcare was another one. As noted by ZDNet's own Joe McKendrick recently, artificial intelligence remained on a steady course of growth and further exploration -- perhaps because of the Covid-19 crisis. Healthcare was a big area for AI investment. Today, the results of a new survey focusing precisely on the adoption of AI in healthcare are being unveiled.

From reducing the burden of back-office admin to offering life-saving potential in diagnoses and treatment recommendations, artificial intelligence (AI) has massive potential to advance healthcare as more and more data becomes available. This new frontier offers a global market expected to be worth US$19.25 billion by 2026. But it's also being approached with a good dose of caution. As organizations strive to leverage the potentially huge benefits of AI in healthcare, the risks of underestimating how to implement these tools safely and effectively alongside human medical professionals remains a key challenge in tapping its full potential. In some cases filling spots where experience, knowledge, even gut-instinct of a medical professional would have served, the decisions made by what can be opaque AI algorithms can be met with suspicion, doubt, or confusion.

Check out David Talby's tutorial "Natural language understanding at scale with spaCy and Spark NLP" at the Strata Data Conference in San Jose, March 5-8, 2018. Registration is now open--save 20% with the code BIGDATA20. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. When I first discovered and started using Apache Spark, a majority of the use cases I used it for involved unstructured text.