Significant technological change often means a cultural shift for...
Leveraging Technologies To Better Position The Business
Reducing And Recovering Your IT Spend
Disrupting the CIO Comfort Zone to Innovate and Transform How...
IT Strategy in Healthcare
Matthew Sena, M.H.A., CIO, Northern Arizona Healthcare
Unleashing the Power of Cloud in Healthcare
Joseph Rostock, CTO, Inovalon
The 3 Ways Software is About to Eat Healthcare
Glen Tullman, CEO, Livongo
Data Science Helps UCHealth Improve Infusion Center and Hospital...
Steve Hess, CIO, UCHealth
Thank you for Subscribing to CIO Applications Weekly Brief
Making the Healthcare Industry Artificially Intelligent
Off late, artificial intelligence (AI) has become the buzzword for almost all industry sectors; this is no different for the healthcare arena. However, AI is a massive infrastructure undertaking, and most organizations get lost in the process of injecting this technology into their IT environment.
As many organizations continue to look at big data analytics to improve healthcare, the scope of machine learning and deep learning solutions in healthcare also increases simultaneously. Machine learning and deep learning are no newbies for the healthcare industry; however, their progress is. This makes AI hard to be deployed and efficiently managed. The lack of ability to efficiently manage AI stops organizations from using real-time analytics at the point of care. The Internet of Things (IoT) in its part is also in need of more powerful analytics infrastructure. Wearable medical devices can evidently reduce the number of patients visiting doctors, as they act as precaution tools, helping the patient analyze his physique. These devices endow physicians with the following benefits; remotely monitor the patients, get a better understanding of the patient’s lifestyle and habits, and collect accurate data. However, organizations that do not have functioning AI solutions cannot obtain, handle, or process this data in real time.
The harder the analytic solutions get to deploy in the healthcare industry, the more promising sign it leaves behind for the future of population health, predictive analytics, and quality patient care