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Home » Here’s how AI is poised to disrupt healthcare – albeit slowly
AI in Finance

Here’s how AI is poised to disrupt healthcare – albeit slowly

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Listen and subscribe to Stocks in Translation on Apple Podcasts, Spotifyor wherever you find your favorite podcasts.

THE the third trimester has just endedand Nvidia’s pure AI business (NVDA) and its flea cohorts suddenly there is a net hang out on the overall performance of the S&P 500 – which itself surprised investors with a solid 5.5% return.

Nevertheless, generative AI is still relevant and slowly moving towards real-world applications.

Abby Yoder, U.S. equity strategist at JPMorgan Private Bank, pointed out that healthcare, which is notoriously slow to move, could be an upcoming candidate for AI-driven innovation.

“Health care has underperformed seven of the last eight years,” Yoder pointed out in a recent episode of Actions in translationalthough the sector is the only one in the S&P 500 to post positive annual earnings growth over the past 21 years.

But Yoder sees AI as a potential key to unlocking a long-awaited disruption that could bring back long-term growth to the sector.

Healthcare stocks have struggled in recent years, a trend Yoder attributes to legacy constraints of legacy systems and obstacles that make it difficult for new technologies to take root. The Byzantine network of actors, rules, regulators, etc. has so far prevented significant adoption of AI, which could potentially address inefficiencies in insurance approvals, manual recordkeeping and claims management, all of which weigh on productivity.

WUHAN, CHINA - APRIL 07: A Da Vinci robot-assisted surgical system is used to play games during the 6th World Health Expo on April 7, 2024 in Wuhan, Hubei province of China. (Photo by VCG/VCG via Getty Images)WUHAN, CHINA - APRIL 07: A Da Vinci robot-assisted surgical system is used to play games during the 6th World Health Expo on April 7, 2024 in Wuhan, Hubei province of China. (Photo by VCG/VCG via Getty Images)

A Da Vinci robot-assisted surgical system is used to play games during the sixth World Health Expo on April 7, 2024 in Wuhan, China’s Hubei province. (VCG/VCG via Getty Images) (VCG via Getty Images)

There are, however, some waves of change. Companies like Google and Microsoft are jumping into this space, collaborate with hospitals and startups to create AI tools that ease this burden.

On the diagnostic sideAI is used to streamline medical imaging, reducing time spent on tasks such as identifying patterns in medical data, improving both the speed and accuracy of patient care. The goal is not to rid the world of human radiologists and technicians, but to give them 21st century tools that lighten their burden and speed up patient diagnoses and recovery.

Proponents of AI say it’s not just about cutting costs; it’s about revolutionizing patient care. Using vast datasets of clinical information, the promise of AI is that one day help predict patient outcomes more effectively, by modeling care before they occur, anticipating complications and selecting treatments.

The other big hope for medical AI bulls is the immense promise of drug discovery.

According to Morgan Stanley Health ForecastTerence Flynn, the company’s director of U.S. biopharmaceutical research, estimates that “(each) 2.5% improvement in preclinical development success rates could lead to more than 30 additional new drug approvals over 10 years,” which would be around $70 billion.

Before the long tail of AI’s promise in healthcare comes to fruition, Yoder highlighted that there are currently strong areas of growth in healthcare, such as the strong performance of GLP-1 drugswhich have placed some pharmaceutical stocks in the same league as their Magnificent Seven AI counterparts. Beyond treating diabetes and obesity, there is still great potential for broad applications in preventive care, particularly in type 2 diabetes, Yoder noted.

The trial data looks promising. “(The) prevention rate from becoming type 2 diabetic is over 98%,” she said.

But despite AI’s potential, significant obstacles remain – and trust is a major obstacle.

More than 55% of healthcare professionals think AI is not ready for prime time medical use, according to a GE Healthcare survey of 7,500 clinicians around the world. And only 26% of U.S. respondents think AI can be trusted, lagging behind the 42% of those responding globally. With real life and death stakes, this represents a major obstacle, along with the network of existing technologies that would need to be integrated. Much of the infrastructure, such as electronic medical records, is outdated and not designed for seamless AI integration.

Another area facing delays is AI-based surgery. While AI-based robots are already helping to remote telesurgerieshumans still drive the bus and the concept of fully autonomous surgical procedures is still far from reality.

Despite industry inertia and barriers to change, Yoder remains optimistic about the growth potential of healthcare as a long-term investment. And if something were to happen to the economy and a soft landing from the Fed, the sector would have a key advantage: it is a large-cap defensive space with low volatility. As Yoder pointed out, not only does health care spending increase as a percentage of GDP, but when a recession hits, health care continues to grow.

On the Yahoo Finance podcast Actions in translationYahoo Finance editor Jared Blikre cuts through the market chaos, noisy numbers, and hyperbole to bring you essential conversations and insights from across the entire investing landscape, providing you with the critical context needed to make the right decisions for your portfolio. Find more episodes on our video center or watch on your favorite streaming service.

Click here for the latest stock news and in-depth analysis, including the events that move stocks.

Read the latest financial and business news from Yahoo Finance

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