Page 41 - February 2017

H EALTHCARE E DUCATION

Artificial Intelligence (AI) in Healthcare: When Can I See My Dr. iRobot?

The concept of artificial intelligence (AI) is not new purposes. Examples include helping analyze genomic
and was made a household term years ago, thanks to sequences, selecting the most optimal pathways for new
movies, TV episodes, and books; however, healthcare was drug development, analyzing real world performance of
perceived too complex to be in the picture. Perhaps the drugs post FDA trial phases in the market, creating cancer
biggest technological factor that brought AI to light in the treatment plans, accurately matching patients to clinical tri-
healthcare field may have been the invention of electronic als, and detecting financial fraud through medical claims
medical records (EMR) that prompted a new field called analysis. Humans could perform all of the above tasks, but
health informatics and gave birth to the digitization of it takes computers just hours to ingest information using
health data. such methods as natural language processing and create
What does this digitization mean? In simple terms, it meaningful output, compared to months and sometimes
helps reduce the number of errors associated with clarity years for humans.
and interpretation of information in patient charts, and Since we seemingly digitized healthcare, possess moun-
transform healthcare provider communications into the BY JACOB KRIVE, PH.D., MBA, MS, AND JENNIE Q. tains of electronic patient data, and can produce complex
21st century. It removes clutter, lowers the cost of care LOU, M.D., M.SC. analysis using statistical formulas and algorithms to gener-
ultimately, and avoids certain types of medical errors. If ate the most effective care plan, the logical question is –
we think of the EMR’s implications further, making when can I make an appointment with my know-it-all com-
patient information digital allows linking patient infor- puter doctor? Well, let’s not rush to place too many
mation into computer databases and opens doors for complex analytics using informa- “iRobots” on the hospital floor just yet: modern artificial intelligence solutions are still
tion about the patient, other patients with similar characteristics, and a wealth of bio- not as smart and flexible as a human brain, so your community doctor would remain
medical knowledge acquired over the years and digitized into computer accessible your best expert when it comes to medical care for years to come. In the meantime, you
knowledge base. These analytics help us with a range of new solutions, from churning might consider healthcare analytics as an exciting and promising career.
out predictive outcomes (what is likely to happen to my patient?) to prescriptive solu- If you are passionate about this new combination of health and information technol-
tions (how can I better help my patient based on information I possess?) to delivering ogy, and are ready to change the world, many educational programs such as the
the most effective and efficient care (what is the clinically best and financially cost effec- Biomedical Informatics program at Nova Southeastern University (NSU) could help you
tive treatment for my patient?), to shifting the emphasis of healthcare to prediction and make the transition. At NSU’s Biomedical Informatics Program, you can get started
prevention (how can individuals be well-informed of what to do in daily living to prevent through its new courses in healthcare data analytics that include curriculum in artificial
certain diseases and maintain health?). intelligence. These newest additions to an existing innovative medical informatics cur-
What artificial intelligence is truly capable of doing today is act like a human brain to riculum are aimed at helping more quantitatively oriented students discover new appli-
supply physicians with myriads of care options, medications, and clinical trials available cations for their talents by developing much needed marketable skills, especially in
around the globe – then narrow it all down to a few top choices and allow human brain health analytics.
to consider what is best for the patient. Algorithms like neural networks and fuzzy logic
are capable of traversing a sea of health information, trained to process and select appli- Dr. Jacob Krive, Adjunct Assistant Professor, Biomedical Informatics Program, College of
cable knowledge in ways similar to a human brain, and churning out solutions much Osteopathic Medicine, Nova Southeastern University, can be reached at jkrive@nova.edu. Dr.
faster than a human even when some of the data elements are missing. And with Big Data Jennie Q. Lou, Professor and Program Director, Biomedical Informatics Program, Professor of
– information from individual sources stored in large computer warehouses for analysis Public Health, Professor of Internal Medicine, College of Osteopathic Medicine, Nova
– making it possible to access all sorts of knowledge and records, for the first time in his- Southeastern University, can be reached at (954) 262-1619 or jlou@nova.edu.
tory, information from multiple domains of medicine can be linked and used for new

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