The age of artificial intelligence (AI) technology is already upon us, taking over a vast majority of tasks that were once performed by us humans alone. As a matter of fact, we already make use of this state-of-the-art tech innovation nearly every day when we talk with an automated phone system or receive real-time traffic alerts on our GPS devices. However, what’s truly commendable is the way in which this technology is working in conjunction with cloud computing to bring about major transformations in the healthcare space.
One recent survey conducted by Statista reported that the global AI market will reach close to $89 billion annually by 2025. A lot of this growth will be fueled by the integration of AI technology into the cloud computing environment.
The snapshot shared below highlights the survey’s forecast with respect to the revenues generated from the AI software market worldwide from 2018 to 2025.
In this article, we explore a few ways the integration of AI and cloud computing can prove to be advantageous for the healthcare industry. But before that, let us review some basic concepts.
What is AI Cloud Computing in Healthcare?
AI cloud computing in the healthcare realm seeks to merge cloud-based computing environments with the machine learning capabilities of artificial intelligence, making connected, intuitive healthcare experiences a reality. Take, for example, the case of Beth Israel Deaconess Medical Center, Harvard University’s teaching hospital, which is using AI to diagnose potentially deadly blood diseases at an early stage so that their effects can be mitigated before they take a toll on the patients.
Doctors at the facility are utilizing AI-enhanced microscopes to detect harmful bacterias such as staphylococcus and E. coli in blood samples at a quicker rate than is possible using manual scanning. The scientists used approximately 25,000 images of blood samples to teach the machines how to search for bacteria. The machines then learned how to identify and predict harmful bacteria in blood with 95 percent accuracy.
This is just the tip of the iceberg and one of the many ways in which this state-of-the-art technology can enhance care. The advancements in AI, along with a well-designed cloud computing environment, can set the stage for more flexibility, efficiency and strategic insight than the world has ever seen.
How an AI Cloud Computing Transform the Healthcare Space?
Today, artificial intelligence tools are rapidly being deployed in healthcare to deliver more value on existing cloud platforms. Some of the advantages that come alongside merging artificial intelligence and cloud computing in healthcare are:
1) Enhanced Clinical Productivity and Improved Access to Care
AI tools, when used in conjunction with cloud servers, can be effectively used to automate a lot of manual processes and streamline tasks for both physicians and their staff. This can rid care providers of less important tasks related to patient documentation and help them focus more on furnishing optimal care solutions while increasing the bottom line of their practice.
Another advantage of using AI cloud computing in healthcare is that it can significantly increase patients’ access to care. The vast majority of Americans reside in remote regions of the country today, and access to care remains an issue of great concern among these rural communities. Digital tools powered by AI and cloud computing are gradually changing this.
For instance, a telemedicine platform powered by cloud technology can easily be used to improve access to care in such regions. AI can then be employed to make sense of the data gathered on such platforms.
AI algorithms can easily detect patterns within this database and help in conducting population health analysis or identifying treatment modalities by studying data from a group of individuals showing similar symptoms. This may greatly improve healthcare outcomes in the long run.
2) Greater Healthcare Cost Savings
In order for advanced AI algorithms to run and derive meaningful results from the data at hand, a lot of processing power is required. This is the very reason it was extremely cost-prohibitive for most healthcare businesses to deploy AI technology in a meaningful manner until recently.
The integration of cloud computing platforms and AI has largely changed the game. It is now possible for even the smallest healthcare practices to experience the power of this solution without having to increase their budgets or dig a hole in their pockets.
Certain AI-enabled systems hold the potential to automatically segregate patient data gathered on merged cloud platforms, enabling physicians and their staff to retrieve it swiftly at a later time. This boosts data interoperability across the organization.
The real savings come when healthcare businesses begin utilizing insights from data gathered to conduct analyses without human intervention, furnish better treatment options or deploy more efficacious procedures. The result is the addition of greater value to the customer experience and an increase of the company’s bottom line.
3) Better Use of Health Data to Improve Population Health Outcomes
Machine learning (ML), a subset of AI, can be optimized for functionality and made more accurate and robust using cloud infrastructure. The flexible resourcing available in the cloud can track more last-mile data from wearables, remote patient monitoring devices and health trackers. This data can then be stored on a cloud server in a cost-effective manner. ML models can then be trained to do heavy-duty analysis of this large amount of data in order to increase their efficiency and improve accuracy over time.
The large amount of data available for training makes ML models scale even better. For several tasks in medical imaging and analysis, for example, the model accuracy is very close to reaching that of humans.
ML models can also be made more personalized to start generating recommendations that are very specific to individual patients. This can especially help improve health outcomes for patients suffering with chronic illnesses, and, in turn, mitigate unnecessary emergency department (ED) visits.
This is truly an exciting time for healthcare leaders to start exploring the potential of AI cloud computing and its implications for improving patient outcomes in the near and not-so-distant future. The integration of cloud technology with artificial intelligence is poised to help us extract more meaningful insights from the massive amounts of health data available in this highly connected world, streamlining complex processes and making patient-centric, value-based care more seamless than ever. The future of healthcare is certainly tied closely to the advancements occurring in AI cloud computing.
About the author: Dr. Leo Langlois is an extensively experienced board-certified physician and surgeon. He graduated from the Warren Alpert Medical School of Brown University, completed his residency training at Walter Reed Army Medical Center (WRAMC) and fellowship trained at UC Davis Medical Center. In addition to his more than 27 years of experience treating chronic disabling conditions and intractable pain, he has run a successful practice since 2003 in Bakersfield, California.