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."
Story by Big Think
Our gut microbiome plays a substantial role in our health and well-being. Most research, however, focuses on bacteria, rather than the viruses that hide within them. Now, research from the University of Copenhagen, newly published in Nature Microbiology, found that people who live past age 100 have a greater diversity of bacteria-infecting viruses in their intestines than younger people. Furthermore, they found that the viruses are linked to changes in bacterial metabolism that may support mucosal integrity and resistance to pathogens.
The microbiota and aging
In the early 1970s, scientists discovered that the composition of our gut microbiota changes as we age. Recent studies have found that the changes are remarkably predictable and follow a pattern: The microbiota undergoes rapid, dramatic changes as toddlers transition to solid foods; further changes become less dramatic during childhood as the microbiota strikes a balance between the host and the environment; and as that balance is achieved, the microbiota remains mostly stable during our adult years (ages 18-60). However, that stability is lost as we enter our elderly years, and the microbiome undergoes dramatic reorganization. This discovery led scientists to question what causes this change and what effect it has on health.
Centenarians have a distinct gut community enriched in microorganisms that synthesize potent antimicrobial molecules that can kill multidrug-resistant pathogens.
“We are always eager to find out why some people live extremely long lives. Previous research has shown that the intestinal bacteria of old Japanese citizens produce brand-new molecules that make them resistant to pathogenic — that is, disease-promoting — microorganisms. And if their intestines are better protected against infection, well, then that is probably one of the things that cause them to live longer than others,” said Joachim Johansen, a researcher at the University of Copenhagen.
In 2021, a team of Japanese scientists set out to characterize the effect of this change on older people’s health. They specifically wanted to determine if people who lived to be over 100 years old — that is, centenarians — underwent changes that provided them with unique benefits. They discovered centenarians have a distinct gut community enriched in microorganisms that synthesize potent antimicrobial molecules that can kill multidrug-resistant pathogens, including Clostridioides difficile and Enterococcus faecium. In other words, the late-life shift in microbiota reduces an older person’s susceptibility to common gut pathogens.
Viruses can change alter the genes of bacteria
Although the late-in-life microbiota change could be beneficial to health, it remained unclear what facilitated this shift. To solve this mystery, Johansen and his colleagues turned their attention to an often overlooked member of the microbiome: viruses. “Our intestines contain billions of viruses living inside bacteria, and they could not care less about human cells; instead, they infect the bacterial cells. And seeing as there are hundreds of different types of bacteria in our intestines, there are also lots of bacterial viruses,” said Simon Rasmussen, Johansen’s research advisor.
Centenarians had a more diverse virome, including previously undescribed viral genera.
For decades, scientists have explored the possibility of phage therapy — that is, using viruses that infect bacteria (called bacteriophages or simply phages) to kill pathogens. However, bacteriophages can also enhance the bacteria they infect. For example, they can provide genes that help their bacterial host attack other bacteria or provide new metabolic capabilities. Both of these can change which bacteria colonize the gut and, in turn, protect against certain disease states.
Intestinal viruses give bacteria new abilities
Johansen and his colleagues were interested in what types of viruses centenarians had in their gut and whether those viruses carried genes that altered metabolism. They compared fecal samples of healthy centenarians (100+ year-olds) with samples from younger patients (18-100 year-olds). They found that the centenarians had a more diverse virome, including previously undescribed viral genera.
They also revealed an enrichment of genes supporting key steps in the sulfate metabolic pathway. The authors speculate that this translates to increased levels of microbially derived sulfide, which may lead to health-promoting outcomes, such as supporting mucosal integrity and resistance to potential pathogens.
“We have learned that if a virus pays a bacterium a visit, it may actually strengthen the bacterium. The viruses we found in the healthy Japanese centenarians contained extra genes that could boost the bacteria,” said Johansen.
Simon Rasmussen added, “If you discover bacteria and viruses that have a positive effect on the human intestinal flora, the obvious next step is to find out whether only some or all of us have them. If we are able to get these bacteria and their viruses to move in with the people who do not have them, more people could benefit from them.”
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
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Embrace the mess: how to choose which scientists to trust
It’s no easy task these days for people to pick the scientists they should follow. According to a recent poll by NORC at the University of Chicago, only 39 percent of Americans have a "great deal" of confidence in the scientific community. The finding is similar to Pew research last year showing that 29 percent of Americans have this level of confidence in medical scientists.
Not helping: All the money in science. Just 20 percent of Pew’s survey respondents think scientists are transparent about conflicts of interest with industry. While this issue is common to many fields, the recent gold rush to foot the bill for research on therapies for healthy aging may be contributing to the overall sense of distrust. “There’s a feeling that at some point, the FDA may actually designate aging as a disease,” said Pam Maher, a neuroscientist who studies aging at Salk Institute. “That may be another impetus for a lot of these companies to start up.”
But partnering with companies is an important incentive for researchers across biomedical fields. Many scientists – with and without financial ties and incentives – are honest, transparent and doing important, inspiring work. I asked more than a dozen bioethicists and researchers in aging how to spot the scientists who are searching for the truth more than money, ego or fame.
Avoid Scientists Who Sound Overly Confident in messaging to the public. Some multi-talented scientists are adept at publishing in both top journals and media outlets. They’re great at dropping science without the confusing jargon, in ways the public can enjoy and learn from.
But do they talk in simple soundbites, painting scientific debates in pastels or black and white when colleagues use shades of gray? Maybe they crave your attention more than knowledge seeking. “When scientists speak in a very unnuanced way, that can be irresponsible,” said Josephine Johnston, a bioethicist at the Hastings Center.
Scientists should avoid exaggerations like “without a doubt” and even “we know” – unless they absolutely do. “I feel like there’s more and more hyperbole and attention seeking…[In aging research,] the loudest voices in the room are the fringe people,” said the biogenerontologist Matt Kaeberlein.
Separate Hype from Passion. Scientists should be, need to be passionate, Johnston explained. In the realm of aging, for example, Leonard Guarente, an MIT biologist and pioneer in the field of aging, told me about his belief that longer lifespans would make for a better world.
Instead of expecting scientists to be lab-dwelling robots, we should welcome their passion. It fuels scientific dedication and creativity. Fields like aging, AI and gene editing inspire the imaginations of the public and scientists alike. That’s not a bad thing.
But it does lay fertile ground for overstatements, such as claims by some that the first 1,000-year-old has already been born. If it sounds like sci-fi, it’s probably sci-fi.
Watch Out for Cult Behavior, some experts told me. Follow scientists who mix it up and engage in debates, said NYU bioethicist Arthur Caplan, not those who hang out only with researchers in the same ideological camp.
Look for whether they’re open to working with colleagues who don’t share their views. Through collaboration, they can resolve conflicting study results and data, said Danica Chen, a biologist at UC Berkeley. We should trust science as long as it doesn’t trust itself.
Messiness is Good. You want to find and follow scientists who’ve published research over the years that does not tell a clean story. “Our goal is to disprove our models,” Kaeberlein said. Scientific findings and views should zig and zag as their careers – and science – progress.
Follow scientists who write and talk publicly about new evidence that’s convinced them to reevaluate their own positions. Who embrace the inherent messiness of science – that’s the hallmark of an honest researcher.
The flipside is a very linear publishing history. Some scientists have a pet theory they’ve managed to support with more and more evidence over time, like a bricklayer gradually, flawlessly building the prettiest house in the neighborhood. Too pretty.
There’s a dark side to this charming simplicity: scientists sometimes try and succeed at engineering the very findings they’re hoping to get, said Charles Brenner, a biochemist at City of Hope National Medical Center.
These scientists “try to prove their model and ignore data that doesn’t fit their model because everybody likes a clean story,” Kaeberlein said. “People want to become famous,” said Samuel Klein, a biologist at Washington University. “So there’s always that bias to try to get positive results.”
Don’t Overvalue Credentials. Just because a scientist works at a top university doesn’t mean they’re completely trustworthy. “The institution means almost nothing,” Kaeberlein said.
Same goes for publishing in top journals, Kaeberlein added. “There’s an incentive structure that favors poor quality science and irreproducible results in high profile journals.”
Traditional proxies for credibility aren’t quite as reliable these days. Shortcuts don’t cut it anymore; you’ve got to scrutinize the actual research the scientist is producing. “You have to look at the literature and try to interpret it for yourself,” said Rafael de Cabo, a scientist at the National Institute on Aging, run by the U.S. National Institutes of Health. Or find journalists you trust to distill this information for you, Klein suggested.
Consider Company Ties. Companies can help scientists bring their research to the public more directly and efficiently than the slower grind of academia, where “the opportunities and challenges weren’t big enough for me,” said Kaeberlein, who left the University of Washington earlier this year.
"It’s generally not universities that can take technology through what we call the valley of death,” Brenner said. “There are rewards associated with taking risks.”
Many scientists are upfront about their financial conflicts of interest – sometimes out of necessity. “At a place like Duke, our conflicts of interest are very closely managed, said Matthew Hirschey, who researchers metabolism at Duke’s Molecular Physiology Institute. “We have to be incredibly explicit about our partnerships.”
But the willingness to disclose conflicts doesn’t necessarily mean the scientist is any less biased. Those conflicts can still affect their views and outcomes of their research, said Johnston, the Hastings bioethicist.
“The proof is in the pudding, and it’s got to be done by people who are not vested in making money off the results,” Klein said. Worth noting: even if scientists eschew companies, they’re almost always financially motivated to get grants for their research.
Bottom line: lots of scientists work for and with companies, and many are highly trustworthy leaders in their fields. But if a scientist is in thick with companies and checks some of the other boxes on this list, their views and research may be compromised.