ABSTRACT
Clinicians in community practice may find it difficult to see the relevance of convolutional neural networks, random forest modeling, clustering, support vector machines, and other esoteric artificial intelligence tools to their everyday responsibilities. They are certainly not the only ones who remain skeptical. Developments in data analytics suggest it may be possible to make screening recommendations more precise and personalized. Analyzing big data sets also offers insights into a variety of other diseases, including multiple sclerosis (MS). Like colorectal cancer and many other disorders, MS is best managed if it can be detected early on. Disease prediction is only one of many potential roles for data analytics. It is also being used to glean insights from telehealth programs, including the personal emergency response systems that have become popular in the elderly community.
