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Artificial Intelligence in Medicine: A New Series Introduction

There’s no way around the fact that humans will be technically outsmarted by machines in the near future, so the best thing we can bring to health care is those traits (like empathy and concern) that are uniquely human.
– Idea embraced by Eric Topol, M.D.

Artificial Intelligence (AI) is a rapidly advancing information technology, and I’m very interested in it. I believe it is comparable to the atomic revolution that began in December, 1942 with the world’s first controlled nuclear reaction, that ultimately unleashed the iconic mushroom cloud over Hiroshima, Japan. The Atomic Age became irreversible—we can never go back.

AI has been in the works for nearly seven decades. Actually, the idea of systematizing human thought and harnessing it within inanimate objects has been around since ancient times. However, a 1956 conference at Dartmouth University gave us the term “artificial intelligence,” and catalyzed a great deal of optimistic enthusiasm over how quickly this new tool would become available.

That initial rosy view dimmed as research funding diminished, but progress was still being made. The earliest examples to gain wide public interest were basically novelties:

  • In 1997, IBM’s supercomputer Deep Blue beat chess grandmaster Gary Kasparov—a blow not just to chess egos but to all who scoffed at the idea of an intelligent machine.
  • In 2011, gameshow prizes were on the line when IBM’s brainchild Watson won TV’s “Jeopardy” quiz show, beating not one but two reigning champions.

Even as I write, AI is already in wide use. If you use social media such as Facebook or Instagram, AI is working in the background to explore thousands of potential connections for you. If you use GPS to get where you want to go, AI plots the best routes for you according to time of day, traffic incidents, and your preferences for road types. And yes, AI is already shaping the future of detection, diagnosis and treatment of diseases.

What is AI?

AI is the process of creating machines with their own intelligence. One component of AI is Machine Learning (ML) which includes specific scientific statistical methods that enable computers to learn on their own, progressively building on their “knowledge” without having to be repeatedly programmed by humans. In turn, a component of ML is Deep Learning (DL) which uses biological models like the brain’s neuron networks that operate bodily systems. With DL, computers can literally teach themselves to perform tasks that our own brains learn to do from birth onward, such as understanding language, recognizing images, and anticipating outcomes.

While AI sounds like something that can serve humanity, brilliant minds like that of the late physicist Stephen Hawking warn us that machines may eventually outsmart us. Some of the creepiest futuristic movies feature supercomputers gone rogue to the near-ruin of their human creators (think of HAL in “2001: A Space Odyssey”). Already, a new specialty in ethics has sprouted in recognition of the need to use AI responsibly, and monitor its development in hopes of preventing machine minds from rebelling against us.

AI in medicine

I am devoting this series of articles to developments in applying Artificial Intelligence—perhaps more aptly termed Augmented Intelligence, since it can enlarge the pool of available information and decision trees—to the clinical practice of medicine.

The American Medical Association (AMA) is the largest association of doctors and medical students in the U.S. They note:

After years of development, machine learning methods have matured enough to be used in clinical medicine. In 2018 the FDA approved software to screen patients for diabetic retinopathy, and the methods are rapidly making their way into other applications for image analysis, natural language processing, EHR data mining, drug discovery, and more.[i]

In their Journal of Ethics, they caution, “Adaptability to change in diagnostics, therapeutics, and practices of maintaining patients’ safety and privacy will be key.” They are justly concerned about “… some of the most ethically complex questions about AI’s implementation, uses, and limitations in health care.”[ii]

My goal is to share some of the most positive ways in which AI is boosting medical research and clinical practice, discuss potential pitfalls, and address the need to integrate the best of medical empathy, compassion, and patient-centered care. In fact, cardiologist/researcher Eric Topol has written a book titled Deep Medicine that reveals how AI can liberate doctors to spend more time with connecting with patients at a level of emotional caring that is often lost due to the demands of documentation, testing, etc.

As with most human-developed technologies, AI has the possibility to become a two-edged sword, subject to the law of unintended consequences. Caution is warranted, but so is hope. What will I conclude? I invite you to watch for coming articles in this series.

NOTE: This content is solely for purposes of information and does not substitute for diagnostic or medical advice. Talk to your doctor if you are experiencing pelvic pain, or have any other health concerns or questions of a personal medical nature.

[i] https://sites.jamanetwork.com/machine-learning/
[ii] https://journalofethics.ama-assn.org/issue/artificial-intelligence-health-care