We’ve been hearing a lot about how Artificial Intelligence (AI), a branch of machine learning (ML) is transforming the healthcare industry, and it’s easy to see why – AI offers unprecedented possibilities for patient care.
From automated appointment reminders to help diagnose diseases and predict medical outcomes, AI technology is revolutionizing the way healthcare is being delivered.
A decade ago, AI and ML were limited to just synthetic speech and chess-playing mechanics. Now, we see more and more companies, especially in the healthcare industry creating applications that make everything a whole lot easier, which is something we’ve also talked about in this guide.
In this blog post, we’ll look at how AI specifically has had tangible impacts on the sector and what opportunities exist for further advancement in the future. In addition to that, we’ll explore some of the successes thus far with real-life case studies as well as ways that have yet to be fully explored.
Why Do We Need AI In Healthcare?
First off, let’s break it down as to why we need technological aspects like Artificial Intelligence and Machine Learning in the first place, especially when we’re talking about healthcare professionals.
Starting, think about the last time you visited a hospital. Getting an appointment can be a hassle, but what’s even more shocking is how most hospitals manage these appointments.
Though it’s much more dominant outside the US, most medical institutions have poor management of the state of affairs, which can mean life and death if you’re in an emergency.
And that’s just one side of the story. In the age of Big Data, the value of patient data is more than just important, and that’s why using algorithms that use AI and ML is important to propel us into the new age of healthcare.
How AI Is Being Used In Healthcare – 2023 and Beyond
Artificial Intelligence being used in healthcare isn’t just a long-term goal that’ll start sometime later – It’s already happening. There are a lot of companies that are using AI technologies to better the healthcare industry, and we’ll explain how.
Machine Learning, in its basic essence, is feeding a lot of data to an algorithm, and training it to do certain things under certain conditions on its own, relieving any human intervention.
Currently, machine learning is used to examine a boatload of medical records and patient data in various healthcare industries,
Natural Language Processing
One of the most dominant uses of AI in the coming years will be symptom-checking using tools, where AI will be strong enough to diagnose patients on its own. In fact, with Natural Language Processing tools and language models like ChatGPT, there are a lot of doctors that are taking AI’s help during patient outcomes.
Dr. Peter Kotanko, head of biomedical evidence generation at the Renal Research Institute (RRI), also explains what the future of AI holds in healthcare organizations.
“Discovering insights in healthcare is no longer restricted to structured lab data or electronic health records. With the help of AI tools like natural language processing, extracting valuable nuggets from unstructured texts is more accessible than ever before.”, he explains in an interview.
Targeted And Personalized Care
With the advancement of technology, the use of AI and ML has become crucial in providing personalized and targeted healthcare. The use of these technologies can enable doctors to make data-driven decisions, which can ultimately lead to better outcomes for patients.
AI and ML can also help in developing precision medicine, which is tailor-made for patients based on their genes, lifestyle, and other factors.
The ability to receive personalized healthcare could have a significant impact on disease prevention, early detection, and treatment, making it a game-changer for healthcare providers to help the public more efficiently.
Top AI Companies In Healthcare To Look Out For
There are a lot of companies out there that are investing their time, and an insane amount of money, into research that goes behind the connection between AI and healthcare. We’ve picked some of the best and most known to give you an idea of what the future holds.
Google Health / DeepMind
Back in 2019, Deepmind’s health care team joined hands with Google Health to further the cause of personalizing health care with AI systems, using health data to avert blindness, and various other causes, and have since made several breakthroughs.
This association between Google Health and DeepMind isn’t just words on paper. They’ve walked their talk, and have created an AI solution that has outperformed human medical professionals in identifying breast cancer, that too by a percentage of 11.5%.
We mentioned before that administrative work, which includes handling patient records and appointments, is not up-to-date in most hospitals, even in modern times like today. That’s where companies like Augmedix come in – A specialist in medical documentation that has developed various administrative tools that use AI to make scheduling, appointments, and everything in between easier.
Their latest venture is something called Augmedix Prep, a charting schedule that reduces the workload on any physician by preparing patient note structures and analyzing previous medical data based on each unique visit.
CloudMedX has been creating waves in the AI and healthcare market ever since its inception, to the point that their product, ONE, also called Health Care In Box, has been awarded as “Best Overall Connected Healthcare Solution” in 2019.
Starting deep in the heart of Silicon Valley, this startup focuses on optimizing financial outcomes, as well as using NLP (Natural Language Processing) to healthcare data, and create better patient outcomes. Learn more about them here, and the healthcare research that they’re doing.
The applications of AI and Machine Learning in the healthcare space are more than just versatile – They’re important. Applications like these are important in propelling us toward the desired future of healthcare, which is automation.
It’s still important to know that AI should be easing up the workflow for medical practitioners and hospitals, as Natalie Schibell, vice president and research director for healthcare at Forrester Research, explains.
“AI is supposed to make the lives of healthcare workers easier. If the process is adhering to the workflow, or adding more screens in the workflow, then it’s best to not use that tool”, she explains.