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Is It Possible For Machine Learning to Help Treat Patients?

Is It Possible For Machine Learning to Help Treat Patients?

There is no denying there is a standing partnership between IT and Healthcare. With costs inflating at a nearly-uncontrollable rate the healthcare industry has started to lean on IT to try and make the delivery of care more efficient. Today, we’ll take a look at healthcare IT, and how the industry is working to use innovative new technologies such as machine learning to provide operational efficiency resulting in better care.

In 2009, U.S. lawmakers mandated the use of information technology as a part of the Health Information Technology for Economic and Clinical Health Act (HITECH Act). The Act, a part of the American Recovery and Reinvestment Act, provides greatly-needed subsidy for healthcare organizations that work to implement IT, specifically electronic health record (EHR) technology, into their service delivery.

For the longest time, many medical administrators considered the use of IT erroneous. That explains why many medical practices just started using IT-fueled systems around a decade ago despite being readily available for the past 25 years. It’s also why it isn’t surprising that as the world around healthcare is inundated with intriguing innovations, the healthcare industry is biding its time. After all, the consequences are literally life and death, and leaving that up to any degree of automation should be handled with pause.

While many of these technologies could be viewed as a fit for the healthcare industry, one has jumped to the forefront and may just be the next big thing in care delivery: machine learning.

For those of you who aren’t familiar with the concept, machine learning is the most basic form of artificial intelligence. The concept is that digital systems, especially ones that are so involved like the EHR, create a lot of data. So much data that it would take human analysts years to compile and analyze it. With this breadth of data being produced, machine learning algorithms can take the data and analyze it. Some algorithms in use today are already performing on the level of an average human physician.

This is largely because the information being sorted is all very specific and gives these rudimentary A.I. systems the chance to provide superior care in some cases. For example, a person goes to their doctor for an ailment. Many general practitioners, while surely good care providers, don’t have the capabilities to be in the know about every medical study, every care option, and all prescription medications that could more effectively treat his/her patient. With machine learning algorithms, these systems can quickly scan new research to provide doctors an on-demand resource that would keep them in the know about important and modern findings by research scientists.

Properly diagnosing and finding treatments for patient ailments is the doctor’s job, and a resource that makes them more effective at doing their job benefits them, their practice, and the patients that depend on his/her expertise. So while the doctor is a very human job, providing them dynamic new resources in which to do their job more effectively is exciting for everyone.

Google and IBM have recognized this and are working on solutions that could change the face of healthcare sooner rather than later. IBM, using the Watson A.I., has partnered with world-class oncology center Sloan-Kettering to develop Watson for Oncology. The system will focus on amalgamating the newest and best information for the treatment of cancer, while incorporating individual patient records, family history, and other information to come up with detailed plans to aggressively treat a patient’s cancer.

It’s only a matter of time before this technology will be used in other parts of the medical field. This technology is state-of-the-art, so it’s not out of the realm of possibility that it will eventually be used to help treat patients with all types of ailments. Are you excited for the future of healthcare using modern artificial intelligence systems? Leave your thoughts in the comments and check back to our blog for more great technology information.

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Monday, October 15 2018

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