posted by ZS
on July 1, 2019
AI is a short acronym that holds the potential to create big change for healthcare delivery heading into a new decade. If you read the news or attend conferences, there’s no shortage of headlines about “radical new diagnosis methods” and countless vendors offering artificial intelligence solutions for anything and everything that ails physicians. In the private sector, healthcare AI startups alone have raised more than $4.3 billion in 576 deals from 2013 to 2018. This number is projected to reach $16.9 billion by 2027.
Artificial intelligence aims to mimic human intelligence using computer systems. The intelligence is built either by self-learning algorithms using data or with the assistance of explicit domain knowledge. The algorithms then keep improving the results by learning from previous outcomes, both positive and negative. But why is it gaining traction now? One of the reasons is the availability of a huge volume of data that can be used to train the AI algorithms. In healthcare, that means data from medical records, lab tests, registries, wearable health apps, and monitoring devices—social determinants of health. Another reason is the exponentially improving computing power, along with better algorithms.