The Algorithm Will See You Now
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."
Indigenous wisdom plus honeypot ants could provide new antibiotics
For generations, the Indigenous Tjupan people of Australia enjoyed the sweet treat of honey made by honeypot ants. As a favorite pastime, entire families would go searching for the underground colonies, first spotting a worker ant and then tracing it to its home. The ants, which belong to the species called Camponotus inflatus, usually build their subterranean homes near the mulga trees, Acacia aneura. Having traced an ant to its tree, it would be the women who carefully dug a pit next to a colony, cautious not to destroy the entire structure. Once the ant chambers were exposed, the women would harvest a small amount to avoid devastating the colony’s stocks—and the family would share the treat.
The Tjupan people also knew that the honey had antimicrobial properties. “You could use it for a sore throat,” says Danny Ulrich, a member of the Tjupan nation. “You could also use it topically, on cuts and things like that.”
These hunts have become rarer, as many of the Tjupan people have moved away and, up until now, the exact antimicrobial properties of the ant honey remained unknown. But recently, scientists Andrew Dong and Kenya Fernandes from the University of Sydney, joined Ulrich, who runs the Honeypot Ants tours in Kalgoorlie, a city in Western Australia, on a honey-gathering expedition. Afterwards, they ran a series of experiments analyzing the honey’s antimicrobial activity—and confirmed that the Indigenous wisdom was true. The honey was effective against Staphylococcus aureus, a common pathogen responsible for sore throats, skin infections like boils and sores, and also sepsis, which can result in death. Moreover, the honey also worked against two species of fungi, Cryptococcus and Aspergillus, which can be pathogenic to humans, especially those with suppressed immune systems.
In the era of growing antibiotic resistance and the rising threat of pathogenic fungi, these findings may help scientists identify and make new antimicrobial compounds. “Natural products have been honed over thousands and millions of years by nature and evolution,” says Fernandes. “And some of them have complex and intricate properties that make them really important as potential new antibiotics. “
In an era of growing resistance to antibiotics and new threats of fungi infections, the latest findings about honeypot ants are helping scientists identify new antimicrobial drugs.
Danny Ulrich
Bee honey is also known for its antimicrobial properties, but bees produce it very differently than the ants. Bees collect nectar from flowers, which they regurgitate at the hive and pack into the hexagonal honeycombs they build for storage. As they do so, they also add into the mix an enzyme called glucose oxidase produced by their glands. The enzyme converts atmospheric oxygen into hydrogen peroxide, a reactive molecule that destroys bacteria and acts as a natural preservative. After the bees pack the honey into the honeycombs, they fan it with their wings to evaporate the water. Once a honeycomb is full, the bees put a beeswax cover on it, where it stays well-preserved thanks to the enzymatic action, until the bees need it.
Less is known about the chemistry of ants’ honey-making. Similarly to bees, they collect nectar. They also collect the sweet sap of the mulga tree. Additionally, they also “milk” the aphids—small sap-sucking insects that live on the tree. When ants tickle the aphids with their antennae, the latter release a sweet substance, which the former also transfer to their colonies. That’s where the honey management difference becomes really pronounced. The ants don’t build any kind of structures to store their honey. Instead, they store it in themselves.
The workers feed their harvest to their fellow ants called repletes, stuffing them up to the point that their swollen bellies outgrow the ants themselves, looking like amber-colored honeypots—hence the name. Because of their size, repletes don’t move, but hang down from the chamber’s ceiling, acting as living feedstocks. When food becomes scarce, they regurgitate their reserves to their colony’s brethren. It’s not clear whether the repletes die afterwards or can be restuffed again. “That's a good question,” Dong says. “After they've been stretched, they can't really return to exactly the same shape.”
These replete ants are the “treat” the Tjupan women dug for. Once they saw the round-belly ants inside the chambers, they would reach in carefully and get a few scoops of them. “You see a lot of honeypot ants just hanging on the roof of the little openings,” says Ulrich’s mother, Edie Ulrich. The women would share the ants with family members who would eat them one by one. “They're very delicate,” shares Edie Ulrich—you have to take them out carefully, so they don’t accidentally pop and become a wasted resource. “Because you’d lose all this precious honey.”
Dong stumbled upon the honeypot ants phenomenon because he was interested in Indigenous foods and went on Ulrich’s tour. He quickly became fascinated with the insects and their role in the Indigenous culture. “The honeypot ants are culturally revered by the Indigenous people,” he says. Eventually he decided to test out the honey’s medicinal qualities.
The researchers were surprised to see that even the smallest, eight percent concentration of honey was able to arrest the growth of S. aureus.
To do this, the two scientists first diluted the ant honey with water. “We used something called doubling dilutions, which means that we made 32 percent dilutions, and then we halve that to 16 percent and then we half that to eight percent,” explains Fernandes. The goal was to obtain as much results as possible with the meager honey they had. “We had very, very little of the honeypot ant honey so we wanted to maximize the spectrum of results we can get without wasting too much of the sample.”
After that, the researchers grew different microbes inside a nutrient rich broth. They added the broth to the different honey dilutions and incubated the mixes for a day or two at the temperature favorable to the germs’ growth. If the resulting solution turned turbid, it was a sign that the bugs proliferated. If it stayed clear, it meant that the honey destroyed them. The researchers were surprised to see that even the smallest, eight percent concentration of honey was able to arrest the growth of S. aureus. “It was really quite amazing,” Fernandes says. “Eight milliliters of honey in 92 milliliters of water is a really tiny amount of honey compared to the amount of water.”
Similar to bee honey, the ants’ honey exhibited some peroxide antimicrobial activity, researchers found, but given how little peroxide was in the solution, they think the honey also kills germs by a different mechanism. “When we measured, we found that [the solution] did have some hydrogen peroxide, but it didn't have as much of it as we would expect based on how active it was,” Fernandes says. “Whether this hydrogen peroxide also comes from glucose oxidase or whether it's produced by another source, we don't really know,” she adds. The research team does have some hypotheses about the identity of this other germ-killing agent. “We think it is most likely some kind of antimicrobial peptide that is actually coming from the ant itself.”
The honey also has a very strong activity against the two types of fungi, Cryptococcus and Aspergillus. Both fungi are associated with trees and decaying leaves, as well as in the soils where ants live, so the insects likely have evolved some natural defense compounds, which end up inside the honey.
It wouldn’t be the first time when modern medicines take their origin from the natural world or from the indigenous people’s knowledge. The bark of the cinchona tree native to South America contains quinine, a substance that treats malaria. The Indigenous people of the Andes used the bark to quell fever and chills for generations, and when Europeans began to fall ill with malaria in the Amazon rainforest, they learned to use that medicine from the Andean people.
The wonder drug aspirin similarly takes its origin from a bark of a tree—in this case a willow.
Even some anticancer compounds originated from nature. A chemotherapy drug called Paclitaxel, was originally extracted from the Pacific yew trees, Taxus brevifolia. The samples of the Pacific yew bark were first collected in 1962 by researchers from the United States Department of Agriculture who were looking for natural compounds that might have anti-tumor activity. In December 1992, the FDA approved Paclitaxel (brand name Taxol) for the treatment of ovarian cancer and two years later for breast cancer.
In the era when the world is struggling to find new medicines fast enough to subvert a fungal or bacterial pandemic, these discoveries can pave the way to new therapeutics. “I think it's really important to listen to indigenous cultures and to take their knowledge because they have been using these sources for a really, really long time,” Fernandes says. Now we know it works, so science can elucidate the molecular mechanisms behind it, she adds. “And maybe it can even provide a lead for us to develop some kind of new treatments in the future.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Blood Test Can Detect Lymphoma Cells Before a Tumor Grows Back
When David M. Kurtz was doing his clinical fellowship at Stanford University Medical Center in 2009, specializing in lymphoma treatments, he found himself grappling with a question no one could answer. A typical regimen for these blood cancers prescribed six cycles of chemotherapy, but no one knew why. "The number seemed to be drawn out of a hat," Kurtz says. Some patients felt much better after just two doses, but had to endure the toxic effects of the entire course. For some elderly patients, the side effects of chemo are so harsh, they alone can kill. Others appeared to be cancer-free on the CT scans after the requisite six but then succumbed to it months later.
"Anecdotally, one patient decided to stop therapy after one dose because he felt it was so toxic that he opted for hospice instead," says Kurtz, now an oncologist at the center. "Five years down the road, he was alive and well. For him, just one dose was enough." Others would return for their one-year check up and find that their tumors grew back. Kurtz felt that while CT scans and MRIs were powerful tools, they weren't perfect ones. They couldn't tell him if there were any cancer cells left, stealthily waiting to germinate again. The scans only showed the tumor once it was back.
Blood cancers claim about 68,000 people a year, with a new diagnosis made about every three minutes, according to the Leukemia Research Foundation. For patients with B-cell lymphoma, which Kurtz focuses on, the survival chances are better than for some others. About 60 percent are cured, but the remaining 40 percent will relapse—possibly because they will have a negative CT scan, but still harbor malignant cells. "You can't see this on imaging," says Michael Green, who also treats blood cancers at University of Texas MD Anderson Medical Center.
The new blood test is sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
Kurtz wanted a better diagnostic tool, so he started working on a blood test that could capture the circulating tumor DNA or ctDNA. For that, he needed to identify the specific mutations typical for B-cell lymphomas. Working together with another fellow PhD student Jake Chabon, Kurtz finally zeroed-in on the tumor's genetic "appearance" in 2017—a pair of specific mutations sitting in close proximity to each other—a rare and telling sign. The human genome contains about 3 billion base pairs of nucleotides—molecules that compose genes—and in case of the B-cell lymphoma cells these two mutations were only a few base pairs apart. "That was the moment when the light bulb went on," Kurtz says.
The duo formed a company named Foresight Diagnostics, focusing on taking the blood test to the clinic. But knowing the tumor's mutational signature was only half the process. The other was fishing the tumor's DNA out of patients' bloodstream that contains millions of other DNA molecules, explains Chabon, now Foresight's CEO. It would be like looking for an escaped criminal in a large crowd. Kurtz and Chabon solved the problem by taking the tumor's "mug shot" first. Doctors would take the biopsy pre-treatment and sequence the tumor, as if taking the criminal's photo. After treatments, they would match the "mug shot" to all DNA molecules derived from the patient's blood sample to see if any molecular criminals managed to escape the chemo.
Foresight isn't the only company working on blood-based tumor detection tests, which are dubbed liquid biopsies—other companies such as Natera or ArcherDx developed their own. But in a recent study, the Foresight team showed that their method is significantly more sensitive in "fishing out" the cancer molecules than existing tests. Chabon says that this test can detect circulating tumor DNA in concentrations that are nearly 100 times lower than other methods. Put another way, it's sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers.
"It increases the sensitivity of detection and really catches most patients who are going to progress," says Green, the University of Texas oncologist who wasn't involved in the study, but is familiar with the method. It would also allow monitoring patients during treatment and making better-informed decisions about which therapy regimens would be most effective. "It's a minimally invasive test," Green says, and "it gives you a very high confidence about what's going on."
Having shown that the test works well, Kurtz and Chabon are planning a new trial in which oncologists would rely on their method to decide when to stop or continue chemo. They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers. The latest genome sequencing technologies have sequenced and catalogued over 2,500 different tumor specimens and the Foresight team is analyzing this data, says Chabon, which gives the team the opportunity to create more molecular "mug shots."
The team hopes that that their blood cancer test will become available to patients within about five years, making doctors' job easier, and not only at the biological level. "When I tell patients, "good news, your cancer is in remission', they ask me, 'does it mean I'm cured?'" Kurtz says. "Right now I can't answer this question because I don't know—but I would like to." His company's test, he hopes, will enable him to reply with certainty. He'd very much like to have the power of that foresight.
This article is republished from our archives to coincide with Blood Cancer Awareness Month, which highlights progress in cancer diagnostics and treatment.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.