The Algorithm Will See You Now
Artificial intelligence in medicine, still in an early phase, stands to transform how doctors and nurses spend their time.
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
New Podcast: Dr. Gigi Gronvall Addresses the Risk of Delta and COVID-19’s Possible Origins
"Making Sense of Science" is a monthly podcast that features interviews with leading medical and scientific experts about the latest developments and the big ethical and societal questions they raise. This episode is hosted by science and biotech journalist Emily Mullin, summer editor of the award-winning science outlet Leaps.org.
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Why Neglected Tropical Diseases Should Matter to Americans
Kissing bugs can carry a parasite called Trypanosoma cruzi, which causes Chagas disease.
Daisy Hernández was five years old when one of her favorite aunts was struck with a mysterious illness. Tía Dora had stayed behind in Colombia when Daisy's mother immigrated to Union City, New Jersey. A schoolteacher in her late 20s, she began suffering from fevers and abdominal pain, and her belly grew so big that people thought she was pregnant. Exploratory surgery revealed that her large intestine had swollen to ten times its normal size, and she was fitted with a colostomy bag. Doctors couldn't identify the underlying problem—but whatever it was, they said, it would likely kill her within a year or two.
Tía Dora's sisters in New Jersey—Hernández's mother and two other aunts—weren't about to let that happen. They pooled their savings and flew her to New York City, where a doctor at Columbia-Presbyterian Medical Center with a penchant for obscure ailments provided a diagnosis: Chagas disease. Transmitted by the bite of triatomine insects, commonly known as kissing bugs, Chagas is endemic in many parts of Latin America. It's caused by the parasite Trypanoma cruzi, which usually settles in the heart, where it feeds on muscle tissue. In some cases, however, it attacks the intestines or esophagus. Tía Dora belonged to that minority.
In 1980, U.S. immigration laws were more forgiving than they are today. Tía Dora was able to have surgery to remove a part of her colon, despite not being a citizen or having a green card. She eventually married a legal resident and began teaching Spanish at an elementary school. Over the next three decades, she earned a graduate degree, built a career, and was widowed. Meanwhile, Chagas continued its slow devastation. "Every couple of years, we were back in the hospital with her," Hernández recalls. "When I was in high school, she started feeling like she couldn't swallow anything. It was the parasite, destroying the muscles of her esophagus."
When Tía Dora died in 2010, at 59, her niece was among the family members at her bedside. By then, Hernández had become a journalist and fiction writer. Researching a short story about Chagas disease, she discovered that it affected an estimated 6 million people in South America, Central America, and Mexico—as well as 300,000 in the United States, most of whom were immigrants from those places. "I was shocked to learn it wasn't rare," she says. "That made me hungry to know more about this disease, and about the families grappling with it."
Hernández's curiosity led her to write The Kissing Bug, a lyrical hybrid of memoir and science reporting that was published in June. It also led her to another revelation: Chagas is not unique. It's among the many maladies that global health experts refer to as neglected tropical diseases—often-disabling illnesses that afflict 1.7 billion people worldwide, while getting notably less attention than the "big three" of HIV/AIDs, malaria, and tuberculosis. NTDs cause fewer deaths than those plagues, but they wreak untold suffering and economic loss.
Shortly before Hernández's book hit the shelves, the World Health Organization released its 2021-2030 roadmap for fighting NTDs. The plan sets targets for controlling, eliminating, or eradicating all the diseases on the WHO's list, through measures ranging from developing vaccines to improving healthcare infrastructure, sanitation, and access to clean water. Experts agree that for the campaign to succeed, leadership from wealthy nations—particularly the United States—is essential. But given the inward turn of many such countries in recent years (evidenced in movements ranging from America First to Brexit), and the continuing urgency of the COVID-19 crisis, public support is far from guaranteed.
As Hernández writes: "It is easier to forget a disease that cannot be seen." NTDs primarily affect residents of distant lands. They kill only 80,000 people a year, down from 204,000 in 1990. So why should Americans to bother to look?
Breaking the circle of poverty and disease
The World Health Organization counts 20 diseases as NTDs. Along with Chagas, they include dengue and chikungunya, which cause high fevers and agonizing pain; elephantiasis, which deforms victims' limbs and genitals; onchocerciasis, which causes blindness; schistosomiasis, which can damage the heart, lungs, brain, and genitourinary system; helminths such as roundworm and whipworm, which cause anemia, stunted growth, and cognitive disabilities; and a dozen more. Such ailments often co-occur in the same patient, exacerbating each other's effects and those of illnesses such as malaria.
NTDs may be spread by insects, animals, soil, or tainted water; they may be parasitic, bacterial, viral, or—in the case of snakebite envenoming—non-infectious. What they have in common is their longtime neglect by public health agencies and philanthropies. In part, this reflects their typically low mortality rates. But the biggest factor is undoubtedly their disempowered patient populations.
"These diseases occur in the setting of poverty, and they cause poverty, because of their chronic and debilitating effects," observes Peter Hotez, dean of the National School of Tropical Medicine at Baylor University and co-director of the Texas Children's Hospital for Vaccine Development. And historically, the everyday miseries of impoverished people have seldom been a priority for those who set the global health agenda.
That began to change about 20 years ago, when Hotez and others developed the conceptual framework for NTDs and early proposals for combating them. The WHO released its first roadmap in 2012, targeting 17 NTDs for control, elimination, or eradication by 2020. (Rabies, snakebite, and dengue were added later.) Since then, the number of people at risk for NTDs has fallen by 600 million, and 42 countries have eliminated at least one such disease. Cases of dracunculiasis—known as Guinea worm disease, for the parasite that creates painful blisters in a patient's skin—have dropped from the millions to just 27 in 2020.
Yet the battle is not over, and the COVID-19 pandemic has disrupted prevention and treatment programs around the globe.
A new direction — and longstanding obstacles
The WHO's new roadmap sets even more ambitious goals for 2030. Among them: reducing by 90 percent the number of people requiring treatment for NTDs; eliminating at least one NTD in another 100 countries; and fully eradicating dracunculiasis and yaws, a disfiguring skin infection.
The plan also places an increased focus on "country ownership," relying on nations with high incidence of NTDs to design their own plans based on local expertise. "I was so excited to see that," says Kristina Talbert-Slagle, director of the Yale College Global Health Studies program. "No one is a better expert on how to address these situations than the people who deal with it day by day."
Another fresh approach is what the roadmap calls "cross-cutting" targets. "One of the really cool things about the plan is how much it emphasizes coordination among different sectors of the health system," says Claire Standley, a faculty member at Georgetown University's Center for Global Health Science and Security. "For example, it explicitly takes into account the zoonotic nature of many neglected tropical diseases—the fact that we have to think about animal health as well as human health when we tackle NTDs."
Whether this grand vision can be realized, however, will depend largely on funding—and that, in turn, is a question of political will in the countries most able to provide it. On the upside, the U.S. has ended its Trump-era feud with the WHO. "One thing that's been really encouraging," says Standley, "has been the strong commitment toward global cooperation from the current administration." Even under the previous president, the U.S. remained the single largest contributor to the global health kitty, spending over $100 million annually on NTDs—six times the figure in 2006, when such financing started.
On the downside, America's outlay has remained flat for several years, and the Biden administration has so far not moved to increase it. A "back-of-the-envelope calculation," says Hotez, suggests that the current level of aid could buy medications for the most common NTDs for about 200 million people a year. But the number of people who need treatment, he notes, is at least 750 million.
Up to now, the United Kingdom—long the world's second-most generous health aid donor—has taken up a large portion of the slack. But the UK last month announced deep cuts in its portfolio, eliminating 102 previously supported countries and leaving only 34. "That really concerns me," Hotez says.
The struggle for funds, he notes, is always harder for projects involving NTDs than for those aimed at higher-profile diseases. His lab, which he co-directs with microbiologist Maria Elena Bottazzi, started developing a COVID-19 vaccine soon after the pandemic struck, for example, and is now in Phase 3 trials. The team has been working on vaccines for Chagas, hookworm, and schistosomiasis for much longer, but trials for those potential game-changers lag behind. "We struggle to get the level of resources needed to move quickly," Hotez explains.
Two million reasons to care
One way to prompt a government to open its pocketbook is for voters to clamor for action. A longtime challenge with NTDs, however, has been getting people outside the hardest-hit countries to pay attention.
The reasons to care, global health experts argue, go beyond compassion. "When we have high NTD burden," says Talbert-Slagle, "it can prevent economic growth, prevent innovation, lead to more political instability." That, in turn, can lead to wars and mass migration, affecting economic and political events far beyond an affected country's borders.
Like Hernández's aunt Dora, many people driven out of NTD-wracked regions wind up living elsewhere. And that points to another reason to care about these diseases: Some of your neighbors might have them. In the U.S., up to 14 million people suffer from neglected parasitic infections—including 70,000 with Chagas in California alone.
When Hernández was researching The Kissing Bug, she worried that such statistics would provide ammunition to racists and xenophobes who claim that immigrants "bring disease" or exploit overburdened healthcare systems. (This may help explain some of the stigma around NTDs, which led Tía Dora to hide her condition from most people outside her family.) But as the book makes clear, these infections know no borders; they flourish wherever large numbers of people lack access to resources that most residents of rich countries take for granted.
Indeed, far from gaming U.S. healthcare systems, millions of low-income immigrants can't access them—or must wait until they're sick enough to go to an emergency room. Since Congress changed the rules in 1996, green card holders have to wait five years before they can enroll in Medicaid. Undocumented immigrants can never qualify.
Closing the great divide
Hernández uses a phrase borrowed from global health crusader Paul Farmer to describe this access gap: "the great epi divide." On one side, she explains, "people will die from cancer, from diabetes, from chronic illnesses later in life. On the other side of the epidemiological divide, people are dying because they can't get to the doctor, or they can't get medication. They don't have a hospital anywhere near them. When I read Dr. Farmer's work, I realized how much that applied to neglected diseases as well."
When it comes to Chagas disease, she says, the epi divide is embodied in the lack of a federal mandate for prenatal or newborn screening. Each year, according to the Centers for Disease Control and Prevention, up to 300 babies in the U.S. are born with Chagas, which can be passed from the mother in utero. The disease can be cured with medication if treated in infancy. (It can also be cured in adults in the acute stage, but is seldom detected in time.) Yet the CDC does not require screening for Chagas—even though newborns are tested for 15 diseases that are less common. According to one study, it would be 10 times cheaper to screen and treat babies and their mothers than to cover the costs related to the illness in later years. Few states make the effort.
The gap that enables NTDs to persist, Hernández argues, is the same one that has led to COVID-19 death rates in Black and Latinx communities that are double those elsewhere in America. To close it, she suggests, caring is not enough.
"When I was working on my book," she says, "I thought about HIV in the '80s, when it had so much stigma that no one wanted to talk about it. Then activists stepped up and changed the conversation. I thought a lot about breast cancer, which was stigmatized for years, until people stepped forward and started speaking out. I thought about Lyme disease. And it wasn't only patients—it was also allies, right? The same thing needs to happen with neglected diseases around the world. Allies need to step up and make demands on policymakers. We need to make some noise."