Feb 26 2020

The Future of Artificial Intelligence in Healthcare

From virtual assistants to MelaFind technology, numerous applications of AI are well positioned to improve patient care and potentially save lives.

Artificial intelligence has come a long way since it was first established as a field in 1956.

Over 60 years ago at Dartmouth College, a group of scholars organized by computer scientist John McCarthy coined the term, said CDW Data Center Architect Ken Cameron during his opening remarks at CDW•G’s AI Showcase at Rutgers University in New Brunswick, N.J. on Tuesday.

The Dartmouth group wanted to explore the possibilities of having machines solve problems that humans typically solved using their natural intelligence, Cameron said. Today, AI has evolved past that early research and development stage. “It’s now affecting our day-to-day lives,” he said.

“And we’re getting to a point where machines can start telling us things we don’t know,” said his co-presenter, Jeremy Wise, a CDW solution architect for AI and deep learning.

That’s certainly true in healthcare, as shown by Dr. Paul Weber, associate dean for continuing medical education at Rutgers’s Robert Wood Johnson and New Jersey medical schools, during a presentation on the present and future clinical applications of AI.

Dr. Weber pointed to several areas where he has seen AI transform the field of healthcare including diagnosis and treatment recommendations, patient communication and care coordination. 

“We’re able to train machines to exhibit humanlike intelligence and apply that in a clinical setting. We haven’t achieved human intelligence, but we’re getting close to it,” he said. 

READ MORE: Discover ways to successfully incorporate AI and ML in healthcare.

Clinical Applications of AI Today and in the Future

There are numerous applications of AI on the market today or awaiting approval that can improve patient care and potentially save lives.

Those applications involve pattern recognition, robotics and natural language processing, which includes speech recognition and translation. Machine learning, a “technique that trains software algorithms to learn from and act upon new data to continuously improve performance,” is also increasingly used today, Dr. Weber said. 

He gave a few examples of the latest tools that leverage AI and its subsets to augment various areas of medicine and healthcare, such as:

  • Virtual assistants: This AI-driven technology can help people with Alzheimer’s disease with their daily activities, Dr. Weber said. For example, 59-year-old Brian Leblanc, who was diagnosed with early onset Alzheimer’s disease in 2014, started using Alexa on his Amazon Echo Dot for reminders to eat, bathe and take medication. “What it enables him to do is to have more control over his life,” Dr. Weber said.
  • MelaFind: This technology uses infrared light to evaluate pigmented lesions. Using algorithms, dermatologists can analyze irregular moles and diagnose serious skin cancers such as melanoma. Although this technology should not replace a biopsy, it helps with giving an early identification, Dr. Weber said.
  • Robotic assisted therapy: Bionik Laboratories in Toronto and Watertown, Mass., use robotics and AI to assist patients in their stroke recovery. A robotic arm and hand use digital algorithms to detect motions that patients can’t execute during therapy and guides them through it. Dr. Weber noted that it can help patients perform more recorded movements per hour than they would have if working with a physical therapist alone.
  • Caption Guidance: The Food and Drug Administration just approved this AI-powered software, which can help medical professionals capture, without any specialized training, echocardiographic images of a patient’s heart that are of acceptable diagnostic quality, Dr. Weber said. Machine learning trains the software to spot high-quality 2D ultrasound images of the heart and even record video clips of it, changing the way heart disease is diagnosed. 

What Medical Professionals Should Consider Before Adopting AI

With this explosion in innovation, it’s important for healthcare professionals and other stakeholders to understand the regulations set in place for the effective development and deployment of these technologies.

“We can’t just put out all of these applications of artificial intelligence without getting approval from regulatory authorities,” Dr. Weber said. 

Agencies have started thinking about how their regulatory framework can adapt to new and evolving technologies, he said. For example, the FDA introduced a new framework last year that enables it to pre-approve manufacturing of adaptive AI-powered software. “It allows for more testing and more rapid approval, and so you’ll see faster turnover, much like the tech industry with smartphones,” Dr. Weber said. 

Medical professionals must also prioritize patient privacy and security when considering AI applications, he said. And despite the growing presence of AI in healthcare, the practitioner-patient relationship still endures, he said. 

“We can talk about all of these devices, but patients still want to talk to their practitioners,” Dr. Weber said. “AI should not replace human interaction — in the end, someone still should be in charge of someone’s care.”

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