How AI Is Revolutionizing the Way We Fight Disease

 Lindsay found herself one of 4 million survivors in her late 30s.

She couldn't say the same about her two aunts. One had fallen victim in her 60s. The other was just 22 when she died. And Lindsay nearly lost her mother, too.

You see, breast cancer runs in her family.

It's the second most common cancer among women in the United States. Roughly 1 in 8 women in the U.S. will develop the disease in their lifetime. And for people like Lindsay, those odds are even higher given her family's proneness to it.

That's why Lindsay decided to take matters into her own hands.

When she was 35, she urged her doctor to screen her for breast cancer.

At first, her doctor was hesitant. She was a few years younger than you'd normally be when you start screening. For example, the U.S. Preventive Services Task Force ("USPSTF") recommends screening every two years starting at the age of 40. And these are changes that've been implemented in just the past year.

Prior to that, the recommendation was to begin at age 50...

To get around these common guidelines, Lindsay fudged how young her mom had been when she was first diagnosed. The doctor gave in. And that little white lie likely helped save her life.

When she went in for her first mammogram at 35, everything looked good.

But about a year later, she found a lump. Based on Lindsay's age, her doctor said it was "likely a cyst."

Cautiously, the doctors ordered an ultrasound to get a better look. Then they decided to do a "3D mammography" exam – a new kind of breast mammogram that uses multiple (low-radiation) images from different angles to build a 3D image of the breast.

This new way of imaging is much more thorough and detailed than a traditional two-dimensional mammogram. It also uses artificial-intelligence ("AI") software to highlight patterns that resemble breast cancers. The software has been "trained" to identify patterns commonly presented during a positive or negative breast cancer mammogram.

These patterns, built from massive databases of anonymous cases, help radiologists make more accurate diagnoses.

After her 3D mammogram, Lindsay's doctor told her right then and there that there was a 99% chance the lump was cancer. And a biopsy later confirmed it.

Lindsay was young. She had a husband and two daughters aged 5 and 7. The news was devastating. But because of the proactive screening, she was able to get early treatment and ultimately beat the cancer.

And that was thanks to medical imaging.

Medical imaging is an indispensable tool today. Not only is it used to find cancer and monitor how subsequent treatments are going, but it can also help diagnose countless other medical ailments...

At its core, medical imaging serves as a linchpin for early disease identification.

It includes technologies like X-rays, CT scans, MRIs, ultrasound, and positron emission tomography ("PET") scans, which unveil intricate details of our internal anatomy. They're crucial to health care professionals when it comes to making diagnoses. They're tools that detect diseases like cancer, heart disease, and neurological disorders.

And when they're applied in the right circumstances and catch a particular disease (like, say, breast cancer) in its early stages, it can make the difference between life and death.

The U.S. imaging-services market was valued at $144.8 billion in 2023. And this market is still growing at a compound annual growth rate ("CAGR") of 4.25%. Given a few factors in the near term, that's set to get even bigger...

You've heard us say it time and again. People are getting older and living longer.

And as the Baby Boomer generation ages, they're more likely to develop chronic conditions and require all kinds of health care services. That includes diagnostic imaging.

Older adults often experience age-related health issues like heart disease, cancer, neurological disorders, and musculoskeletal conditions. These ailments often end up needing regular monitoring and diagnostic assessments. That means higher demand for imaging services like MRIs, CT scans, X-rays, and ultrasounds.

In the coming year, the medical community will hit a bleak milestone. The first-time new cases of cancer in the U.S. are expected to cross the 2 million mark. That's almost 5,500 cancer diagnoses a day.

A lot of that has to do with the aging Baby Boomers and general growth in the population. You can see this in the chart below...

There has also been a rise in diagnoses of six of the 10 most common cancers – breast, prostate, endometrial, pancreatic, kidney, and melanoma. (The other four of the top 10 cancers are lung, colorectal, bladder, and non-Hodgkin lymphoma.)

In men, the most common types of cancer – prostate, lung, and colorectal – account for almost one-half (48%) of all cancer cases. In women, the most common types of cancer –breast, lung, and colorectal – account for almost 51% of all cancer cases.

Colorectal cancers aside, the remaining most common forms of cancers for men and women are diagnosed through common imaging equipment in a radiology clinic.

The good news is that there are increasingly more options to treat these devastating diseases. That's especially true if you catch them early.

Over the past 30 years, the risk of dying from cancer has steadily declined. That's in part due to fewer people smoking... but it's also because of early detection and new treatments. According to the American Cancer Society, this has led to 4 million people in the United States surviving who otherwise would not have.

The mortality rate of prostate cancer dropped in half from 1993 to 2013 as a result of advanced screening and treatment. Following a peak in 1989, the number of women who have died of breast cancer has decreased by 43%.

And now we're starting to see medical imaging and AI advancements transform health care diagnostics and revolutionize how diseases are detected, diagnosed, and treated.

The detailed pictures from CT scans, MRIs, and PET scans generate vast amounts of data. AI – especially "deep learning" algorithms – can analyze this data efficiently. It can uncover insights that a radiologist might miss.

You see, AI algorithms are trained on large datasets to recognize complex patterns. This improves the accuracy and speed of disease diagnosis.

You can think of an algorithm as a set of instructions. As it relates to imaging, it might recognize an abnormality in the breast or the heart. It uses existing information (the data) to understand these abnormalities.

Ultimately, it helps health care professionals make informed decisions and give better care to patients.

Take mammograms, for example. A false positive can lead to unnecessary medical intervention and a whole lot of anxiety for the patient.

In a recent study published in Nature, a deep-learning-based AI system was trained using mammograms from about 90,000 women in the U.S. and Europe. The AI system had about a 3% decrease in the number of false-positive results compared with the findings provided by radiologists.

The other advantage is that AI can process large volumes of medical-imaging data quickly and efficiently. That helps health care professionals save time and make faster decisions.

And that's especially important today...

Hospitals, imaging centers, and outpatient facilities are all facing a worldwide shortage of radiologists.

Factors like the COVID-19 pandemic, burnout leading to early retirements or career shifts in health care, and increased demand for imaging as the population ages are putting pressure on already scarce radiology professionals.

The Association of American Medical Colleges' seventh annual analysis of physician supply and demand noted that the shortage of radiologists and other specialists could be more than 35,000 by 2034.

AI can reduce turnaround time for reading images by as much as 83% in some cases. That's a lifeline for busy radiologists. It helps automate tedious tasks like reporting and follow-up scheduling, allowing radiologists to focus on more complex, high-level work. It augments radiologists' expertise in the search for anomalies in images.

Two years ago, I launched my newsletter Prosperity Investor to focus on investing in health care. And I predicted the medical industry was going to lead to huge gains. Not only have all of the predictions I made come true, but the results are even better than I could have expected. And the triple-digit gains I've helped subscribers earn are only the beginning.

Last Friday, I released a new video to share how the recent strides made in AI technology are impacting health care and why even bigger gains could be on the way.

Click here for all the details.

Here's to our health, wealth, and a great retirement,

Dr. David Eifrig and the Health & Wealth Bulletin Research Team

June 3, 2024