The Advancement of Design: The Rise of AI
For ages computer scientists have been trying to push the limits of programing to create AI systems with the human-level intelligence from their ever-expanding knowledge pools to decision making abilities. However, results were limited as the system was only as advanced as the knowledge added to it.
The new approach is to create systems that are capable of learning by extracting rules and evaluating cause and results from the data fed to them and direct observation from choices made. With a base provided by traditional AI protocols and big data, augmented by deep learning and predictive analytics, an evolution of healthcare methodology is dawning.
A faster and more reliable trend line, or risk score can be achieved through predictive analytics driven by enhanced AI systems, resulting in a heightened personalized healthcare program that could prevent the declining of health through Predictive Healthcare.
What is Personalized Healthcare and How is it Different from Personalized Medicine?
Before we get into where AI fits into all of this, we need to separate two very different categories from each other; Healthcare and Medicine.
Isn’t healthcare and medicine the same thing?
No, these two things may seem to be the same, but they are, in fact, very different.
Personalized Medicine is using your descriptive data to figure out the right drug, at the right time with the right dose to treat whatever is ailing you. It focuses on using descriptive analytics.
Think of it as just making use of historical data as descriptive analytics does not include forecasting or trending. It is simply the process of turning raw data into a report. It is just matching your personal profile with the ailment to address the current situation. It leaves a lot to be desired in terms of preventative healthcare as it’s only preventing further decline rather then preventing the decline entirely. That’s where Personalized Healthcare comes in, as it uses Predictive Analytics to assess an accurately detailed, precise trend line of potential health risks, often referred to as a Risk Score.
The key difference between healthcare and medicine here is the ability to extrapolate the course of future events from descriptive data, in order to tell a provider what is likely to happen soon, which can only be done through incorporating Big Data, and AI Deep Learning technology to derive what is known as Predictive Analytics.
Predictive analytics is revolutionizing the healthcare industry as we can now treat to prevent decline rather than treat to prevent further decline.
Personalized Healthcare Through AI Predictive Analytics
Let’s use Personalized Healthcare Programs to treat illnesses before they fully occur, but there’s no guarantee that they will even acquire this illness so how can you treat for it?
Simple, we cheat, and by cheat, I mean we use Predictive Analytics derived from Enhanced AI functions.
Using a solution based on predictive machine learning will enable of huge amounts of data over large time periods from multiple projects and use correlations and statistics to come up with more precise estimates. This implies that with experience comes knowledge and expertise, which the AI can leverage in a far greater capacity.
By using this new technology, we can address potential health issues on the likelihood of occurrence by referencing the individual’s descriptive data against vast scores of other descriptive data and assessing the change of progression towards different health issues from trends shown from others of similar profiles.
The objective of using Predictive Analytics is that we can improve long-term engagement and reduce the risks associated with chronic diseases, which will lead to more preventative care and less post-manifestation treatment, an end goal for healthcare.
While everyone is different, there are common risk factors for every illness that when addressed and mitigated, significantly lower the chance of occurrence or minimize the effects of manifestation when it does occur. It is at this point the Predictive Healthcare takes on a new form called Prescriptive Healthcare, which using prescriptive analytics derives the optimal treatment methods.
The Goal: Prescriptive Healthcare
Prescriptive Healthcare can be thought of as an approach like Predictive Healthcare but goes one step ahead of where Predictive Analysis is replaced with Prescriptive Analysis. This is where Personalized Medicine meets with Personalized Healthcare as Prescriptive analytics. It can tell a user what course of action would produce the highest likelihood of maximum benefit when a predicted event does occur, which ties flawlessly into Personalized Medicine’s approach.
This proactive approach allows you to more efficiently address your client’s needs reducing the costs of time and energy. Since AI has access to Big Data and Deep Learning capabilities it can identify patterns and trends too complex for humans or other automated techniques. Since the AI is aware of the current standings of each patient a change in one area allows for the AI to react and prescribe advisable treatment options based on these markers we may miss.
As a result, the client gains peace of mind as they no longer need to worry since we ‘understand their needs,’ and we can accurately assess growing risk factors and address them before they become major health concerns.
The outlook of such AI advancements would change how healthcare is approached in its entirety. Although AI isn’t there yet from prediction to prescription, it has reached this point in Personalized Medicine, and thus it is only a matter of time until Personalized Healthcare becomes common place.