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."
Stacey Khoury felt more fatigued and out of breath than she was used to from just walking up the steps to her job in retail jewelry sales in Nashville, Tennessee. By the time she got home, she was more exhausted than usual, too.
"I just thought I was working too hard and needed more exercise," recalls the native Nashvillian about those days in December 2010. "All of the usual excuses you make when you're not feeling 100%."
As a professional gemologist, being hospitalized during peak holiday sales season wasn't particularly convenient. There was no way around it though when her primary care physician advised Khoury to see a blood disorder oncologist because of her disturbing blood count numbers. As part of a routine medical exam, a complete blood count screens for a variety of diseases and conditions that affect blood cells, such as anemia, infection, inflammation, bleeding disorders and cancer.
"If approved, it will allow more patients to potentially receive a transplant than would have gotten one before."
While she was in the hospital, a bone marrow biopsy revealed that Khoury had acute myeloid leukemia, or AML, a high-risk blood cancer. After Khoury completed an intense first round of chemotherapy, her oncologist recommended a bone marrow transplant. The potentially curative treatment for blood-cancer patients requires them to first receive a high dose of chemotherapy. Next, an infusion of stem cells from a healthy donor's bone marrow helps form new blood cells to fight off the cancer long-term.
Each year, approximately 8,000 patients in the U.S. with AML and other blood cancers receive a bone marrow transplant from a donor, according to the Center for International Blood and Marrow Transplant Research. But Khoury wasn't so lucky. She ended up being among the estimated 40% of patients eligible for bone marrow transplants who don't receive one, usually because there's no matched donor available.
Khoury's oncologist told her about another option. She could enter a clinical trial for an investigational cell therapy called omidubicel, which is being developed by Israeli biotech company Gamida Cell. The company's cell therapy, which is still experimental, could up a new avenue of treatment for cancer patients who can't get a bone marrow transplant.
Omidubicel consists of stem cells from cord blood that have been expanded using Gamida's technology to ensure there are enough cells for a therapeutic dose. The company's technology allows the immature cord blood cells to multiply quickly in the lab. Like a bone marrow transplant, the goal of the therapy is to make sure the donor cells make their way to the bone marrow and begin producing healthy new cells — a process called engraftment.
"If approved, it will allow more patients to potentially receive a transplant than would have gotten one before, so there's something very novel and exciting about that," says Ronit Simantov, Gamida Cell's chief medical officer.
Khoury and her husband Rick packed up their car and headed to the closest trial site, the Duke University School of Medicine, roughly 500 miles away. There they met with Mitchell Horowitz, a stem cell transplant specialist at Duke and principal investigator for Gamida's omidubicel study in the U.S.
He told Khoury she was a perfect candidate for the trial, and she enrolled immediately. "When you have one of two decisions, and it's either do this or you're probably not going to be around, it was a pretty easy decision to make, and I am truly thankful for that," she says.
Khoury's treatment started at the end of March 2011, and she was home by July 4 that year. She say the therapy "worked the way the doctors wanted it to work." Khoury's blood counts were rising quicker than the people who had bone marrow matches, and she was discharged from Duke earlier than other patients were.
By expanding the number of cord blood cells — which are typically too few to treat an adult — omidubicel allows doctors to use cord blood for patients who require a transplant but don't have a donor match for bone marrow.
Patients receiving omidubicel first get a blood test to determine their human leukocyte antigen, or HLA, type. This protein is found on most cells in the body and is an important regulator of the immune system. HLA typing is used to match patients to bone marrow and cord blood donors, but cord blood doesn't require as close of a match.
Like bone marrow transplants, one potential complication of omidubicel is graft-versus-host disease, when the donated bone marrow or stem cells register the recipient's body as foreign and attack the body. Depending on the severity of the response, according to the Mayo Clinic, treatment includes medication to suppress the immune system, such as steroids. In clinical trials, the occurrence of graft-versus-host disease with omidubicel was comparable with traditional bone marrow transplants.
"Transplant doctors are working on improving that," Simantov says. "A number of new therapies that specifically address graft-versus-host disease will be making some headway in the coming months and years."
Gamida released the results of the Phase 3 study in February and continues to follow Khoury and the other study patients for their long-term outcomes. The large randomized trial evaluated the safety and efficacy of omidubicel compared to standard umbilical cord blood transplants in patients with blood cancer who didn't have a suitable bone marrow donor. Around 120 patients aged 12 to 65 across the U.S., Europe and Asia were included in the trial. The study found that omidubicel resulted in faster recovery, fewer bacterial and viral infections and fewer days in the hospital.
The company plans to seek FDA approval this year. Simantov anticipates the therapy will receive FDA approval by 2022.
"Opening up cord blood transplants is very important, especially for people of diverse ethnic backgrounds," says oncologist Gary Schiller, principal investigator at the David Geffen School of Medicine at UCLA for Gamida Cell's mid- and late-stage trials. "This expansion technology makes a big difference because it makes cord blood an available option for those who do not have another donor source."
As for Khoury, who proudly celebrated the anniversary of her first transplant in April—she remains cancer free and continues to work full-time as a gemologist. When she has a little free time, she enjoys gardening, sewing, or maybe traveling to national parks like Yellowstone or the Grand Canyon with her husband Rick.
Paralyzed By Polio, This British Tea Broker Changed the Course Of Medical History Forever
Robin Cavendish in his special wheelchair with his son Jonathan in the 1960s.
In December 1958, on a vacation with his wife in Kenya, a 28-year-old British tea broker named Robin Cavendish became suddenly ill. Neither he nor his wife Diana knew it at the time, but Robin's illness would change the course of medical history forever.
Robin was rushed to a nearby hospital in Kenya where the medical staff delivered the crushing news: Robin had contracted polio, and the paralysis creeping up his body was almost certainly permanent. The doctors placed Robin on a ventilator through a tracheotomy in his neck, as the paralysis from his polio infection had rendered him unable to breathe on his own – and going off the average life expectancy at the time, they gave him only three months to live. Robin and Diana (who was pregnant at the time with their first child, Jonathan) flew back to England so he could be admitted to a hospital. They mentally prepared to wait out Robin's final days.
But Robin did something unexpected when he returned to the UK – just one of many things that would astonish doctors over the next several years: He survived. Diana gave birth to Jonathan in February 1959 and continued to visit Robin regularly in the hospital with the baby. Despite doctors warning that he would soon succumb to his illness, Robin kept living.
After a year in the hospital, Diana suggested something radical: She wanted Robin to leave the hospital and live at home in South Oxfordshire for as long as he possibly could, with her as his nurse. At the time, this suggestion was unheard of. People like Robin who depended on machinery to keep them breathing had only ever lived inside hospital walls, as the prevailing belief was that the machinery needed to keep them alive was too complicated for laypeople to operate. But Diana and Robin were up for the challenges – and the risks. Because his ventilator ran on electricity, if the house were to unexpectedly lose power, Diana would either need to restore power quickly or hand-pump air into his lungs to keep him alive.
Robin's wheelchair was not only the first of its kind; it became the model for the respiratory wheelchairs that people still use today.
In an interview as an adult, Jonathan Cavendish reflected on his parents' decision to live outside the hospital on a ventilator: "My father's mantra was quality of life," he explained. "He could have stayed in the hospital, but he didn't think that was as good of a life as he could manage. He would rather be two minutes away from death and living a full life."
After a few years of living at home, however, Robin became tired of being confined to his bed. He longed to sit outside, to visit friends, to travel – but had no way of doing so without his ventilator. So together with his friend Teddy Hall, a professor and engineer at Oxford University, the two collaborated in 1962 to create an entirely new invention: a battery-operated wheelchair prototype with a ventilator built in. With this, Robin could now venture outside the house – and soon the Cavendish family became famous for taking vacations. It was something that, by all accounts, had never been done before by someone who was ventilator-dependent. Robin and Hall also designed a van so that the wheelchair could be plugged in and powered during travel. Jonathan Cavendish later recalled a particular family vacation that nearly ended in disaster when the van broke down outside of Barcelona, Spain:
"My poor old uncle [plugged] my father's chair into the wrong socket," Cavendish later recalled, causing the electricity to short. "There was fire and smoke, and both the van and the chair ground to a halt." Johnathan, who was eight or nine at the time, his mother, and his uncle took turns hand-pumping Robin's ventilator by the roadside for the next thirty-six hours, waiting for Professor Hall to arrive in town and repair the van. Rather than being panicked, the Cavendishes managed to turn the vigil into a party. Townspeople came to greet them, bringing food and music, and a local priest even stopped by to give his blessing.
Robin had become a pioneer, showing the world that a person with severe disabilities could still have mobility, access, and a fuller quality of life than anyone had imagined. His mission, along with Hall's, then became gifting this independence to others like himself. Robin and Hall raised money – first from the Ernest Kleinwort Charitable Trust, and then from the British Department of Health – to fund more ventilator chairs, which were then manufactured by Hall's company, Littlemore Scientific Engineering, and given to fellow patients who wanted to live full lives at home. Robin and Hall used themselves as guinea pigs, testing out different models of the chairs and collaborating with scientists to create other devices for those with disabilities. One invention, called the Possum, allowed paraplegics to control things like the telephone and television set with just a nod of the head. Robin's wheelchair was not only the first of its kind; it became the model for the respiratory wheelchairs that people still use today.
Robin went on to enjoy a long and happy life with his family at their house in South Oxfordshire, surrounded by friends who would later attest to his "down-to-earth" personality, his sense of humor, and his "irresistible" charm. When he died peacefully at his home in 1994 at age 64, he was considered the world's oldest-living person who used a ventilator outside the hospital – breaking yet another barrier for what medical science thought was possible.