Artificial Intelligence

AI Is Transforming Health Diagnoses, But the Market Faces Challenges

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When it comes to jobs likely to be replaced by robots, most people wouldn’t think of medical professionals — but recent innovations might just be giving them a run for their money. With many hospitals across the globe facing long waiting times and shortages of medical professionals, artificial intelligence might just be coming to save the day.

AI could solve many of the health sector’s greatest problems by providing faster and more accurate diagnoses of health conditions. However, the potential privacy concerns and regulatory barriers make it less than straightforward to implement. How should interested investors proceed?

A quick guide to AI in healthcare 

One of artificial intelligence’s most powerful use cases is machine learning, which teaches machines to analyze data to find patterns and make predictions. And when it comes to the world of healthcare, there’s no shortage of patient data available.

AI could analyze the information healthcare providers have regarding diagnoses and symptoms of previous patients, and use this to diagnose patients demonstrating the same symptoms. It may even be able to pick up on symptoms common among all diagnosed patients that medical professionals have missed.

One of its most promising potential use cases is radiology, which uses imaging technology to diagnose patients. AI could improve radiology tools like X-rays by noticing complex patterns and processing images more quickly than people can do now.

Considering the high numbers of errors involved in diagnosing conditions and the fact many medical professionals are overworked, this could be a valuable lifeline.

Where it’s being used

Given the potential of AI for health diagnostics, it shouldn’t come as a surprise that many companies are vying to become providers of the tech. 

One of the most promising companies in the space is Babylon Health (BBLN), a tech company focusing on digital health. It has found a new way to use machine learning to diagnose disease: AI symptom checkers that use causal reasoning rather than correlations in machine learning, which had previously been the norm.

Another firm to watch is Nine Health Global, which was founded in 2016 and focuses on the use of big data and AI to improve global health. It has been regulated by the FDA and achieved a good reputation in the industry, but is currently privately owned.

Google (GOOGL) previously got into the space with Google Health, and one of its focuses was AI tools for diagnostics. It has since been shut down due to challenges, but it’s worth keeping an eye on whether Google tries to make its comeback.

Although some hospitals have tried out AI as a diagnostic tool for doctors to use (although it’s far from replacing them still) as part of trials. However, there’s still a lag with adoption — for some of the reasons we’ll mention shortly. 

Risks of AI

We’ve briefly hinted at some of the concerns in the world of diagnostics using AI, and maybe you can guess them yourself.

One of the biggest problems is privacy concerns. There’s a potential for an abuse of power here — for instance, a company could sell health data to firms that sell products to people with certain conditions. Also, the use of the internet for such sensitive data could increase the risk of ransomware attacks, meaning patient information would end up in the hands of malevolent actors. Ideally, the medical provider should have sole control of the data unless consent is given to transfer it elsewhere.

It’s also important for companies to comply with regulation — and given the complexity of the field, this could involve the FTC, FDA, and HIPAA. However, the technology is currently developing faster than regulations, which has contributed to a lag in hospitals using the tools.

Stanford University found that proposals for regulatory frameworks aren’t where they need to be yet as they don’t address the need to build trust and there’s insufficient rigor in evaluation.

Should you invest?

The potential of AI for health diagnostics is clear. 5% of outpatients receive an incorrect diagnosis, yet AI has been found to be far better. One AI model identified lung cancer on CT scans 95% of the time, compared to a 65% success rate among human professionals. It can also work 24/7, which allows it to identify threats more quickly.

Some researchers believe that the market could be worth $9.38 billion by 2029. However, given the challenges, investors need to look out for companies that are proactive in working with regulators and which have proper privacy policies. The fact that even Google’s efforts have failed shows that this is a tough market — but it’s also an important market, which means it has a high chance of sticking around.

A healthy market ahead?

In an area as complicated as AI for health diagnostics, it’s tough to predict exactly what the sector will look like in a few years time. Due to the potential of the technology, it’s likely that it will play some role — but the companies that achieve success will have to pay close attention to regulations and privacy concerns. Investors should focus attention here rather than getting blinded by technological innovation.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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David Cotriss

David Cotriss is an award-winning writer of over 500 news and feature articles on business and technology. His LinkedIn profile can be found at

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