Jul 11 2023
Data Analytics

What Types of AI Are Being Used in Healthcare?

Artificial intelligence can be classified in two ways. Experts explain how current AI tools used in healthcare can be classified and what the future may hold.

The idea of visiting an AI-powered robot for your medical care may still be the stuff of Hollywood movies, but artificial intelligence is far from fictional in the healthcare industry. Providers and researchers widely use AI-powered tools designed to improve clinical efficiencies, prevent errors and advance treatments. 

“AI is a support and augmentation tool,” explains Dr. Mona Flores, the global head of medical AI at NVIDIA, “and it’s up to us to harness its power for the good.”

HealthTech spoke with three industry leaders about the types of AI used in healthcare, the benefits for providers and patients, and what medical professionals need to keep in mind when adopting AI.

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What Are the Different Categories of Artificial Intelligence?

AI can be categorized in two ways, based on functionality and intelligence.

The first category classifies AI by system type:

1. Reactive 

As the most basic form of AI, a reactive machine responds to external stimuli but does not form memories and cannot learn from past experiences.

2. Limited Memory 

Nearly every AI tool used today falls into this category. A limited-memory machine builds on available data to learn and make future predictions.  

3. Theory of Mind  

Hypothetically, a theory of mind machine would identify, understand and respond to human emotions.

4. Self-Aware AI

Also theoretical, a self-aware machine would think for itself and be conscious of its own emotions and desires.

DISCOVER: Tips for avoiding four common AI mistakes.

The second category classifies AI by level of intelligence:

1. Artificial Narrow Intelligence

All current AI tools have artificial narrow intelligence. They are designed to perform specific functions and cannot think for themselves. 

2. Artificial General Intelligence

At this level, the machine would be able to think like a human, perform multifunctional tasks and make independent decisions. 

3. Artificial Superintelligence

Artificial superintelligence currently exists only in movies and books. At this level, the machine would be self-aware and have capabilities that surpass human abilities. 

EXPLORE: Five steps to analytics and AI success.

What Are the Main Use Cases of AI in Healthcare Today?

The healthcare industry uses limited memory AI in several areas:

Clinical Documentation 

ChatGPT is the most well-known generative and natural language processing tool. Chatbots powered with similar technology are used to help patients assess symptoms and book appointments, and can assist with outpatient monitoring.

Providers also use versions of this type of AI for clinical documentation. One example is Nuance’s Dragon Ambient eXperience. The program records and transcribes doctor-patient interactions and writes a comprehensive clinical summary in the electronic health record

“The more technology can handle the administrative work, the more time physicians have to actually practice medicine,” says Ken Harper, Nuance’s vice president and general manager of healthcare virtual assistants and ambient clinical intelligence. “Having AI do a portion of the work also minimizes the clinician’s cognitive burden and fatigue.”

Harper adds that this type of AI improves access to care for patients. “We’ve seen healthcare organizations use some of that time to bring more patients through the door.”


Imagine 10 million radiologists analyzing a scan, as opposed to just a handful of specialists. That’s essentially how AI works with healthcare imaging. Platforms such as Nuance’s Precision Imaging Network, for example, use AI algorithms to process images and provide suggestions to radiologists.

“AI is in almost everything that we’re doing with imaging today,” Flores says, noting that it may help reduce diagnostic mistakes by detecting anomalies a human might overlook.

AI’s advantage is that it can learn from an unfathomable amount of data. An AI tool that has learned all the ways a disease can present itself in an imaging study can very quickly derive answers from new imaging studies — and it won’t get tired while doing so, as a human would.

Patient Monitoring 

Medical providers have been able to expand remote patient monitoring because of wearable devices that use AI to track and analyze data such as blood pressure, glucose levels and sleep patterns. 

Virtual nursing platforms such as the ones offered by Artisight and Caregility use smart technology to monitor large numbers of patients. The AI tool can be trained to detect potential problems, play automated messages to patients and alert in-person care teams.

Ryan Cameron, vice president of technology and innovation at Children’s Hospital & Medical Center in Nebraska, says his organization is developing AI-driven systems to automate decision support for providers. “One of our goals is to ensure critical patients receive the medications they truly need.”

To achieve this, Cameron explains, “we have a project focused on real-time monitoring of vital signs. The AI tool compares the patient’s data against multiple sources, runs complex math and makes infusion recommendations for doctors to review.”


It usually takes several years for novel drug therapies to be developed for actual patient use, but generative AI tools such as the NVIDIA BioNeMo Service can speed up the drug discovery process.

With BioNeMo, “we’re able to quickly generate candidate drugs and test them in a simulation environment, made possible by AI and accelerated computing,” Flores explains. “We can shorten the cycle and make it less expensive to develop drugs for rare diseases.” 


Surgeons use AI-powered robotics for minimally invasive procedures. “We do a high volume of laparoscopic surgeries using the da Vinci Surgical System,” Cameron says. 

“It’s hard for a person to achieve perfect stillness because of breathing and heart rate. The da Vinci system absorbs the surgeon’s natural body movements and makes sure everything happens with great precision.”

What Does Healthcare Need to Know About AI?

“AI will revolutionize everything — certainly, patient outcomes,” Cameron predicts, “and it will redefine our expectations of clinical efficiencies.”

But, he adds, “The big challenge with AI is ensuring there is a healthcare-specific code of ethics and a regulatory environment. We need to ensure the use of AI is always safe and clinically proven.”

Flores also urges a level of caution. “AI is not magic. Like everything else, you have to test it and run clinical trials to ensure the solutions actually work in the real world.”

Harper reiterates that although AI is a highly useful tool, at this stage final medical decisions remain in the hands of human professionals. “Do I personally think this technology will get to a point where it makes the decisions and automatically administers care? No, I don’t see that,” he says. “But I do think AI can help with everything in between, and that’s where there’s a massive opportunity in healthcare.”

UP NEXT: Find out how AI and automation are supporting clinicians.

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