What is machine learning?
There’s a good chance you’ve heard the term “machine learning,” but, if you’re like most people, you might not know exactly what it means. Machine learning (ML) is one form of artificial intelligence (AI), and it refers to software that has self-learning or self-improving capabilities — in other words, computers that can learn without humans intervening or assisting.
Part of our everyday lives
If you’ve ever received a fraud inquiry from your credit card company asking about a suspicious charge, you’ve experienced the results of ML. Likewise if you’ve received movie recommendations based on your viewing history from a streaming service.
How machine learning works
ML uses historical and real-time data to take action and can either minimize the need for or augment human judgment. How it works depends on your goal. For example, you may be trying to:
- Classify patients or members into one group or another, helping identify the number of patients who are at risk for a specific condition, such as COPD
- Identify outliers in a large group of data, like the handful of suspicious reimbursement claims mixed in with millions of accurate ones
When you know the desired output of the model ahead of time, it is called "supervised" learning.
ML can also be used when you don't know what you're looking for ahead of time, which is called "unsupervised" learning. This approach is good for answering open-ended questions, like “which service lines should we invest in to increase our market share?” or “which members are most likely to engage when offered a treatment plan?” The output from the model will use existing patterns within the data to help leaders uncover potentially new areas for investment or new understanding.