Artificial intelligence is making waves in countless industries, with the healthcare sector recently joining this list. In fact, a recent report by McKinsey showed that AI is now a priority for global healthcare-decision makers and to date, healthcare-related AI funding has reached $8.5 billion.
The potential impact that AI can have on healthcare is life-changing, particularly because of its ability to mimic cognitive functions.
Along with improving patient outcomes, introducing AI into the healthcare sector can also make medical assistance more affordable and easily accessible.
What does this mean for medical practitioners though? Could the medical world change as we know it over the next decade?
Incorporating AI into Healthcare
With the speed at which AI advancements are taking place, it’s only natural to wonder whether bots would eventually replace human doctors.
Realistically, human medical professionals will never be replaced. However, AI can make it possible for human doctors to make better decisions.
Big Data is gradually changing the healthcare sector by making it easier to incorporate AI into day-to-day practices. AI’s use of sophisticated algorithms makes it possible for bots to learn, assist, and self-correct. What’s more, an AI system’s learning capabilities means it gets better over time, reducing the margin for error.
With enough development and advancements, AI systems may even eventually be able to predict potential health risks based on data.
Many professionals wonder whether incorporating AI into the healthcare sector is really necessary though.
A number of studies show that human error is one of the leading causes of medical mishaps and even death.
A John Hopkins study showed that a quarter of a million deaths in the U.S. were caused by medical errors in 2016. Another survey indicated that one in 10 doctors reported making a major medical error in the space of 3 months.
Stats like these are enough reason to incorporate AI technology into the healthcare sector.
AI will never replace human compassion and skill, but it has the potential to radically change the medical sector.
The Positive Impact of AI on the Healthcare Sector
AI is already positively impacting the medical industry, but there is still a lot that can be done.
Here are some of the ways that AI is currently being applied and will be used to alter healthcare going forward.
Patient Risk Identification
With the help of AI, healthcare practitioners can identify at-risk patients more easily using historical data. Reducing patient re-admissions and the cost thereof is one of the goals of combining AI and patient data.
In-Depth Medical Imaging Analysis
Another way that AI is helping medical professionals is through the examination of images such as MRIs, CT scans, and X-rays. Using advanced diagnostic processes, AI bots can find things that the human eye might miss. This too helps reduce the margin of error in a healthcare environment.
What’s more, fully automated systems can read and interpret medical images after hours or in areas that are understaffed.
Virtual Medical Assistance
Voice and chat-based interactions are a solution that multiple organizations are working on. By virtually answering patient questions, it reduces the need to see a doctor in person. One potential fallback that still requires work and research is ensuring patient safety and efficacy using these virtual solutions.
There are also a number of solutions developing around bots that can assist patients with appointments, medication, and 24/7 patient support.
Genome Mapping Enhancements
When combined with AI, it’s possible to use genomics to detect cancer and vascular diseases much earlier on. It can even make patients aware of potential health concerns based on their genes. Add onto this AI’s assistance with medical parts machining and the margin of error can once again be greatly reduced.
The Problem with Subjective Data
In most other sectors, data is measured accurately. In healthcare, on the other hand, data is mostly subjective.
As we progress and make AI a bigger part of healthcare, data inaccuracy needs to be considered.
For one, it is not always easy to read a physician’s notes. Data sources also vary, which makes it difficult to create comprehensive patient profiles. Not all patients willing offer up information on their health or history either, another factor that could impact treatment efficacy and patient safety.
How to best protect patients when combining subjective data and machine-learning technology is still a key consideration as AI moves into the healthcare sector. How to regulate virtual healthcare is another.
Overall, artificial intelligence is the way forward in healthcare, but there are still a few issues and concerns to overcome.
