Clinicians can make better sense of their data with properly applied business analytics, as running a medical facility is highly complex.  AI can then also help avert security disasters by scouring unstructured data, helping to reverse the harm caused by human error, misuse, hacking and physical theft.

Though we have made incredible recent progress in the medical field, there are countless parties making countless attempts at developing cures and new treatments for the maladies that still continue to plague us. Connecting the data from those tests and experiments has proven difficult, but AI allows us to view them in conjunction and make new insights and observations.

Machine learning can also be useful in healthcare use cases.   Incorporating speech recognition and Natural Language Processing (NLP) to record clinical content can assist in workflow, reduce errors and ultimately make medical data more accessible to patients.

Because of the private and personal nature of medical documents and information, as well as the rules regarding the disclosure of medical information, data security in the medical field is of the utmost importance. There are strict laws in the world of AI as well regarding health care data, and both medical professionals and their clients can rest easily knowing their information is safely secured.  Apply predictive analytics and deep learning to predict fraud and detect suspicious behavior in or near real-time.