The right diagnosis can save a life. See how cognitive computing can ensure that more people get the treatments they need before it’s too late.
Healthcare is a field that is always, and should always, be changing and developing. New medicines, procedures, and ways to interact with patients are continuously being developed and used to improve treatment. Technology is often a major player in developing medicine and is used in many procedures, including preventative care and surgeries.
One development on the horizon of technology in healthcare is with cognitive computing: the simulation of human thought through a computerized system. You might have seen cognitive computing in action before when IBM’s Watson debuted as a contestant on Jeopardy back in 2011.
Since then, software experts have created additional cognitive computing systems, and the technology is being developed to do much more than answer trivia—it’s going to revolutionize the way we prevent and treat chronic illness.
Cognitive computing systems like Watson work differently than just a regular search engine. While a standard search engine searches based on a stored system of organized data, cognitive computing systems work on a system of non-organized data imputed with more natural language.
The system takes that data and learns from it by processing it critically, similar to how the human brain does. Unlike the average human brain, though, it can hold and process much more information and sort through it at a faster rate.
Since it can decipher search queries written or said in colloquial language, it becomes a much more useful search tool than a Google-type search engine in this context. With so much information and knowledge in the world, this is quickly becoming the system for information storage.
Healthcare is a field that can greatly benefit from the addition of cognitive computing. There is an abundance of medical information out there, and it’s always changing and growing. Medical professionals can diagnose and treat chronic diseases better than ever before, but as the medical knowledge base continues to grow rapidly, it’s becoming increasingly difficult to keep up.
New treatments, new diagnoses, and new discoveries—there is no way your average general practitioners, or even specialists, are going to be able to memorize and configure all of that information as it comes.
This is one of the main ways cognitive computing will come into play. Doctors will be able to use the system as a more intelligent search engine Google: entering in inquiries and bringing up and analyzing the results. They will be able to spend less time in school memorizing symptoms and diseases, and focus more on interpreting the health data for diagnosis and implementing treatments.
Since systems like Watson can hold and decipher vasts amount of information with more natural language search capabilities and in multiple languages, this makes it an optimal system for keeping the ever-growing medical field of knowledge.
Doctors and other medical professionals will help manage the information entered to ensure it’s as accurate and detailed as possible. From there physicians can use the information system to help accurately diagnose patients based on their symptoms and medical history.
When doctors enter these factors into the system, the AI can offer up possible diagnoses and ways to treat. It is then up to the doctor to take that information, interpret it, and apply it to the patient. This is going to give doctors the ability to be more accurate in their prognosis and spend more time with and treating their patients.
According to an article from Bradley University, the improvements in technology will not only benefit doctors, but also nurses. Implementing electronic health records (EHRs) will streamline the process of recording and entering patient information. Nurses can then focus more on patient care and interaction rather than paperwork.
EHRs are a vital part of the cognitive computing system as they grant the system the ability to take a patient’s wellness information and enter it into the overall database. This then allows the system to use and compare with studies and other patient information to better analyze and learn for diagnostic purposes.
Take a patient at the University of Tokyo for example. Doctors incorrectly diagnosed her malady, but after running her genetic changes through Watson’s database, Watson diagnosed her with a rare form of leukemia in just ten minutes. She was then able to receive the proper treatment.
With the addition of wearable technology like fitness trackers and other health tech, healthcare providers are getting a more accurate depiction of patient health. One such example is a New Jersey man whose Fitbit health data helped his doctors make a life or death decision. Entering this data into the EHRs use by cognitive computing systems will also be an important part of the system learning and diagnosing.
One of the main concerns when talking about EHRs and data mining systems like Watson is security. Security is a primary concern for any large database, like those used in large corporations, and have been susceptible to data breaches. It’s only natural that people will be uncomfortable with the idea that a widely accessible database will include their most intimate and private information.
What people need to know is that systems like Watson have several layers of security, and any patient information made available for diagnostic analysis is anonymous. The artifical intelligence system will use that anonymous information to learn from so it can make better comparisons for diagnosing others with similar health problems. The benefits of sharing this information are integral to the functionality and accuracy of the system, and the only people who will have access to the database is healthcare professionals.
The incorporation of cognitive computing into the healthcare field is revolutionizing the way we can care for and treat people medically. As the systems become the standard in medical facilities, it will decrease the amount of time needed to diagnose, and increase the efficiency of medical professionals. This will only help the cost of medical care for the better, and have a positive impact on patients.
Mila Sanchez is a writer and a recent graduate of Boise State University. She enjoys traveling, studying foreign languages, and taking pictures of her dog, Baymax. Connect with her on Instagram and Twitter.