World Reimagined

How Artificial Intelligence Is Transforming Healthcare

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Credit: Photo by National Cancer Institute on Unsplash

Artificial Intelligence (AI) is already transforming industries from banking and retail to transportation and energy and has the potential to significantly improve every industry it touches. Since some version of “improve my health” will likely be near the top of many New Year’s resolution lists next month, here are some ways AI is being used in healthcare.

Will the machines take over? 

Before we go any further, let’s address the big fear that accompanies every major leap in technology. Will AI cause mass unemployment? From what we are seeing so far, the answer is a definitive no, and here is an example of why. Back in 2017, Alphabet’s (GOOG) DeepMind Go-playing AI defeated the world’s number one human player, Ke Jie, by winning the first two games in a three-part match. If you haven’t already seen the documentary AlphaGo on YouTube and want to understand more about AI, I highly recommend it. The defeat was an emotional blow to the global Go-playing community, but the fallout was not what many expected. AlphaGo had taught itself to play using strategies that had never been seen before, which ended up improving the sophistication of the game as played by those who studied the famous match, raising the bar for everyone. What we learned from the experience is that rather than replacing us, AI can be used to spark innovation, to see things in novel ways that the human brain may not. AI is simply the next tool in mankind’s ongoing quest to augment our own capabilities, just as was the case with the wheel, the ax, the steam engine, the abacus and the La-Z-Boy (LZBrecliner.

Why Now? 

Investing in AI is making new record highs.

  • Worldwide funding for AI companies hit a record $66.8 billion in 2021, more than double the total in 2020, according to CB Insights, with healthcare accounting for about a fifth of the overall funding. While quarterly AI funding did decline 12% from Q4 of 2021 to Q1 of 2022, it was significantly less than the 19% decline in total funding over that same period.
  • Gartner Research estimates that global healthcare IT spending in 2021 reached $140 billion, with AI and robotic process automation identified as the top spending priorities.

The past year has seen a profound acceleration in AI capabilities, many of which are illustrated in this year’s State of AI report. Today, for example, there are 18 drugs in clinical trials that have been developed using an AI-first approach. In 2020 there was not a single one.

Experts believe we are at an inflection point. For example, Jeffrey Dean, a Google Senior Fellow and Distinguished Fellow at the Stanford University Institute for Human-Centered Artificial Intelligence wrote a paper this spring called, “A Golden Decade of Deep Learning” in which he looks at the “tremendous” progress made in AI over the past decade and what we may expect in the future.

The future impact will be profound. PWC estimates that by 2030, AI could contribute $15.7 trillion to the global economy. The healthcare sector is particularly in dire need of improvement, representing around a fifth of the total U.S. economy in 2020higher than any other country, while having significantly worse outcomes than most. The U.S. Health System is ranked 69th in the world by the Legatum Institute and has an average life expectancy well below most developed nations. Accenture estimates that by 2026, AI applications could potentially generate $150 billion in annual savings for the U.S. healthcare system. 

Healthcare Administration

The U.S. has the highest per capita healthcare spend but below average outcomes, making Healthcare Administration a prime area for improvement. Administrative expenses are estimated to account for somewhere between 15% and 25% of total national healthcare costs. Here, AI can be used to both streamline processes and detect fraud, similar to the way banks detect unusual transactions. One of the companies offering solutions in this field is Oracle (ORCL), which offers AI to improve operations, the patient experience, healthcare finances and healthcare data management.

Synthetic Data

AI algorithms learn by analyzing huge amounts of data, but in some areas of the economy, the data it needs is heavily restricted due to compliance or privacy concerns, creating the need for Synthetic Data. Synthetic data is realistic, but not real. It can be defined as “annotated information that computer simulations or algorithms generate as an alternative to real-world data,” and while it may be artificial, research is finding that it can be as good or even better for training an AI model. According to Gartner Research, by 2030, Synthetic Data will likely surpass real data in AI models. Israel-based MDClone, a synthetic medical data startup, raised $63 million earlier this year and is working with MCI Onehealth Technologies (DRDR.TO) to convert MCI’s real-world datasets into synthetic files that while entirely artificial, are statistically comparable to the original data, thus can be used in research without any privacy concerns. This isn’t happening just in healthcare, but also in other data-sensitive sectors such as financial services where, for example, JP Morgan (JPM) is training financial AI models with fake data. 


One of the most powerful applications of AI in healthcare is in diagnostics, where it has the potential to scan better and faster than even the best diagnosticians. For example, about 90% of those who develop breast cancer have no known genetic mutation, making the disease’s emergence highly unpredictable. The Massachusetts Institute of Technology has developed Mirai, an artificial intelligence system that has been, for example, able to scan a mammogram and flag the patient as being at high risk for breast cancer within the next five years. The flagged patient had indeed developed breast cancer just four years after the image had been taken. Other algorithms have been developed to predict lung cancer by looking at CT scans or heart disease by looking at MRI images earlier than is possible for a human alone.

Digital Diagnostics has developed an AI technology that evaluates images of the back of a patient’s retina to evaluate the extent of damage to blood vessels due to diabetic retinopathy, typically without the need for the eyes to be dilated. Similarly, the company also has an AI product that can detect serious skin conditions earlier, when they are more treatable, but difficult to for the human eye to detect.

Medtronic (MDT) is the exclusive distributor for the first FDA authorized AI-assisted system for colonoscopy, developed by Cosmo Pharmaceutical (CMOPF). The system is available in Europe, parts of Asia, Australia and the Middle East. The system, GI Genius, identifies regions of the colon within the endoscope’s view where colorectal polyps might be located. I think we can all agree that if one is undergoing the joy of a colonoscopy, we’d prefer it to be as effective and efficient as possible.

These solutions, far from replacing doctors, will instead give more time for patient interaction rather than spending hours poring over images themselves looking for signs of disease or abnormalities in blood samples. Doctors will be able to spend more time treating and less time diagnosing. 

AI Chips 

We cannot talk about AI without mentioning the microchips that make these AI applications possible. The roughly $21 billion AI microchip market was once dominated by Nvidia (NVDA) but is becoming increasingly competitive. Some of the other major players include Advanced Micro Devices, Inc. (AMD)IBM (IBM), Intel (INTC) and Micron Technology (MU). The sector is attracting many startups as well, such as Cerebras Systems, which claims to have built the largest chip in existence, with 2.6 trillion transistors and 850,000 AI cores, to power what it says is the fastest AI accelerator to date. Others include Horizon Robotics and SambaNova Systems

The Impact of Artificial Intelligence on Healthcare

Artificial intelligence (AI) is being used to tackle some of the most pressing problems in healthcare. AI can help reduce costs, improve efficiency and outcomes, promote medical research, and above all—improve patient care.

  • Reduce costs: AI systems can identify patients who are at risk earlier and flag them for further testing or intervention. This prevents costly mistakes that might otherwise go undetected.
  • Improve efficiency: In hospitals where nurses spend more than half their time doing administrative tasks such as scheduling appointments, managing medications and communicating with doctors about previous cases, an automated system could take over these tasks freeing up valuable time for other patient-centric activities like visiting patients in person or providing emotional support during difficult times.
  • Improve outcomes: AI algorithms can analyze large amounts of data from different sources to track patterns that may lead to better treatment options for individualized cases based on specific symptoms (e.g., identifying patients who could benefit from surgery instead of medication). They also provide real-time analysis capabilities, so health workers can immediately make decisions when they need it most – especially important when lives are at stake. By identifying problems earlier, when they are more easily treated, outcomes will be improved and lives saved.

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

Lenore Elle Hawkins

Lenore Elle Hawkins has, for over a decade, served as a founding partner of Calit Advisors, a boutique advisory firm specializing in mergers and acquisitions, private capital raise, and corporate finance with offices in Italy, Ireland, and California. She has previously served as the Chief Macro Strategist for Tematica Research, which primarily develops indices for Exchange Traded Products, co-authored the book Cocktail Investing, and is a regular guest on a variety of national and international investing-oriented television programs. She holds a degree in Mathematics and Economics from Claremont McKenna College, an MBA in Finance from the Anderson School at UCLA and is a member of the Mont Pelerin Society.

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