July 14, 2024

Holistic Pulse

Healthcare is more important

Leveraging AI For Good In The Healthcare Industry

5 min read

Seema Kumar is the CEO of Cure.

Artificial intelligence has garnered a lot of buzz over the last year, rightfully so, for its potential to revolutionize many industries, including healthcare. I believe AI-driven tools could be a game changer in improving human health and solving health inequities that persist in underserved communities in the United States and globally. But we’re facing one big risk: If we don’t collaborate, share data and design AI algorithms correctly, the technology could exacerbate disparities in health outcomes rather than solve them.

The U.S. continues to grapple with a host of inequities that touch every corner of our healthcare system. Black and Hispanic Americans are less likely to receive interventions for heart attacks than white Americans, for example, and Black women are more likely to die from pregnancy complications than white women. Hispanic and Native American adults have twice the risk of developing kidney failure compared to white Americans, while Black Americans’ risk is four times higher.

AI is already in use in domains such as diagnostics, patient monitoring, mathematical modeling and simulation predictions. Researchers are applying it in early-stage drug design and discovery and the identification of biomarkers for diseases. During the height of the Covid-19 pandemic, scientists used AI, data sciences and computing to track where virus hotspots were likely to emerge to try to stay one step ahead.

Yet it seems we have only scratched the surface of what AI can do in healthcare. Our team is exploring the powerful ways that AI can help address health inequities and improve healthcare experiences and outcomes for all patients.

Health AI For Good

Last year, in collaboration with our partner, MIT Solve, we launched a challenge with the theme “Health AI for Good.” We called on entrepreneurs and teams to develop new and innovative ideas that responsibly and equitably use AI across specialties, disciplines and sectors to advance health solutions.

Our challenge finalists illustrate how AI might address inequities from several different angles, while reinforcing key themes that will continue to inform health innovation in 2024 and beyond:

Disease Awareness and Early Detection

Some finalists are working to improve disease awareness and early detection among underserved populations, including through:

• AI tools that can predict kidney disease risk and create preventive treatment plans.

• AI-facilitated cardiovascular health screenings in trusted community spaces for Black patients.

• Data from electronic health records that can identify and screen patients in underserved communities with elevated cancer risk.

Diagnostic Testing

AI holds great potential for improving diagnostic testing and access to diagnostics. Other innovators are exploring ideas such as:

• AI tools that can improve the detection of fetal abnormalities in ultrasound images and simplify

ultrasound technology so any medical professional can provide the service to pregnant women, even in nontraditional medical settings.

• A robotic arm that can produce and send ultrasound images to specialists anywhere in the world.

• An AI assistant that mimics a molecular tumor board, an interdisciplinary panel of experts that guides clinical decision making in oncology.

Access to Therapies

Additional finalists are investigating how AI can improve patient access to quality healthcare through:

• A service that provides “AI social workers” that can simplify scheduling wellness visits and health screenings for low-income families while enrolling them in assistance programs.

• An AI software platform that can predict optimal conditions for cell and gene therapy development.

• An open-source AI platform that aims to uncover previously unidentified links between diseases and drugs to identify new applications for existing medications.

What’s Next For AI In Healthcare

We use the term artificial intelligence, but I like to think of it as augmenting human intelligence. I predict that in the near future, we will discover more new applications for AI in healthcare, including:

• Predictive modeling: Autonomously performing thousands of calculations to help monitor and manage patients’ health conditions, such as type 1 diabetes.

• Radiology advances: Giving human experts access to huge stores of data and computation capabilities to better diagnose and treat diseases.

• Early interventions: Accelerating our ability to calculate warning signs and predict diseases at earlier stages, such as Alzheimer’s.

I see three main advantages in this next chapter of the AI healthcare revolution:

1. Enhanced Pandemic Preparedness

The last four years have been enormously challenging for all of us, and pandemic fatigue is real. Yet we know that future pandemics are a serious threat, and we must learn lessons from the experience we’ve just been through as a global community.

AI has the potential to prevent a future pandemic—which could protect not just one person’s health but an entire population and our public health system. We were understandably proud that we developed and released Covid-19 vaccines so quickly, but in the future, our goal would be to never reach that stage at all. AI could enable rigorous monitoring, allowing us to detect a disease early, create a rapid response and quickly prevent it from spreading.

2. Protective Analytics

People are now living longer, but they are not necessarily living healthier into old age. AI-based protective analytics would help us detect, prevent and treat diseases much earlier than we are today.

More than 6 million people are living with Alzheimer’s in the U.S., for example, and that number is projected to rise to close to 13 million by 2050. If we could identify the disease and intervene earlier, a significant percentage of older adults could live healthier, happier and more productive lives.

3. Improved Patient Experience

In hospitals and healthcare systems, patients can often feel lost when navigating their own care plans. AI has the potential to create a completely different patient journey, one in which people feel empowered to understand and use their personal data as active participants in decision making.

If we combine data visualization with AI, we could process complex health information and translate it in a way that is understandable to a layperson, enabling patients to make informed decisions about their care, instead of depending on the healthcare system to decide for them.

AI is a transformational tool, and it offers exciting opportunities to solve our toughest healthcare challenges. If we continue to explore AI’s enormous potential, we can make strides toward improving health outcomes for all.

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