AI in Healthcare: Current Trends and Predictions About the Future

The global Artificial Intelligence (AI) market for healthcare is set to reach $17.8 billion by 2025, a recent Zion Market report predicts. According to the report, the market, which is currently valued at around $4 billion, is growing at a 43.8% CAGR and set to pass the $6 billion mark somewhere in 2021.

These figures give the clearest indication that AI in healthcare is destined for big things in the coming years. Indeed, International SOS says that American medical startups acquired as much as $1 billion in AI funding in the last 12 months alone, further proving the importance of AI going forward.

So, the question we’re left with is – where exactly is this money going? What AI solutions can we look forward to, and in which areas of healthcare?

We’ve looked at data from the top healthcare research resources, including Gartner, Deloitte, and the US National Library of medicine. Here’s what’s evident;

Trends in Medical AI

Medical AI primarily helps caregivers, patients, and administrators make informed clinical decisions. Through machine learning (ML), AI provides techniques to uncover complex associations that can be reduced to problem-solving equations. AI is currently playing a pivotal role in the following areas;

• Patient risk identification 

As already mentioned, one of the critical capabilities of AI is the analysis of vast amounts of data. By analyzing historical patient data, AI has recently been used to provide real-time support to clinicians to help assess patient risk.

AI, for instance, is now used to identify re-admission risk. In some hospitals, the technology identifies patients likely to return to the hospital within 30 days of discharge. AI has also proved valuable in determining the risk of cardiovascular diseases based on the still images of a patient’s retina.

• Radiology 

Artificial intelligence is also demonstrating its value in radiology. A few AI solutions have been developed to help with image analysis and diagnosis. One of the things AI does in these circumstances is to highlight potential areas of interest on a scan so that the radiologist can focus on these areas, thus not only boosting efficiency but also reducing human error.

Additionally, AI has also shown that it’s possible to automate the entire image analysis process. AI solutions can read and interpret a scan without human input. What’s even better is that the technology is proving to be better than humans at image analysis. Recent demonstrations show a higher success in tumor detection on MRIs and CTs.

• Precision health 

Precision health is widely considered the next step in healthcare provision. The main difference between traditional care and this new approach to care is that precision care formulates customized treatment strategies based on an individual’s background and condition. It takes into account people’s genes, environment, lifestyles, and past health records to develop a precise solution for each individual patient.

AI is at the center of precision health. Using information generated from wearable devices and advanced electronic health systems, AI-enabled precision health tools can identify potential risks and even suggest preventive interventions.

• Remote care

Remote care is a branch of telehealth that allows for continuous monitoring of a patient’s condition and performance outside of a medical facility. Mobile devices are used to measure vital signs and the results transmitted to caregivers. If abnormalities are detected, the caregiver can respond appropriately.

One of the ways AI boosts remote care is by enabling the creation of virtual doctors. Patients can tell these virtual assistants how they feel as well as report on their progress. The assistants can also ask questions and relay vital information on how the patient can better manage their health.

• Administrative duties 

Finally, AI is also already playing a few administrative roles in the modern healthcare setup. First, AI healthcare bots that use natural language processing (NLP), sentiment analysis, and concept extraction algorithms have found their way into healthcare. These solutions can respond to patient statements and questions on things like appointment scheduling, bill payment, and medical refills.

Additionally, AI is helping physicians take more accurate and comprehensive notes through specialized, real-time decision support models.

The Future Promises Even More Breakthroughs

The above applications are just some of the standout examples of what AI can do healthcare. There are likely to be even more applications in the different facets of healthcare in the future.

According to the World Economic Forum, for instance, by 2030, healthcare providers will rely significantly on AI to handle day to day business. Among other things, the World Economic Forum predicts;

• AI-powered predictive care: AI and predictive analytics will come together to help us anticipate when a person is at risk of falling sick or developing a chronic disease.
• Networked hospitals and connected care: The hospital will no longer be one large building. Instead, we’ll have retail clinics, same-day surgery centers, and specialist clinics – all connected to a single digital infrastructure – with AI at the center of it all.
• Improved patient and staff experiences: AI will also help reduce wait times, improve staff workflows, and take on the ever-growing administrative burden. The result? Happier staff and more satisfied customers!

Considerations Before Adopting AI

Given the endless potential benefits, you might already be thinking about rolling out AI at your medical facility. This would be a great step. It’s also a great time to leap. However, there are a few considerations to keep in mind.

First, you need approval from the FDA to start using AI-powered software for healthcare purposes. Before you seek approval, it would help to read the agency’s guidance document on submitting a 510 (k).

Secondly, medical professionals who decide to adopt AI solutions are reminded to prioritize patient privacy and security. Even as we usher in technological solutions to the field, the practitioner-patient privacy must, especially, endure.

Finally, a serious challenge of AI adoption is a cultural one. Although even today AI predictive and diagnostic abilities, as well as treatment assignments, based on the huge set of statistical data collected from the millions of previous patients, are more precise than ones made by a doctor, people have less trust in a computer than to a doctor. Both medical practice and patients can benefit from AI implementation, but in order to do this, tech companies, doctors, and hospitals have to go a long path proving the efficiency of this technology. This is one of the biggest challenges we have to solve in the nearest future. 

Role of NIX in Healthcare AI

NIX Solutions is a leader in emerging healthcare solutions, including artificial intelligence (AI). We monitor the markets and are always at the forefront in helping practices and facilities adopt and roll out new solutions. Partnering with us, therefore, gives a competitive edge. Сontact us today for a free consultation. We will be happy to help.