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."
A Rare Disease Just "Messed with the Wrong Mother." Now She's Fighting to Beat It Once and For All.
Amber Freed felt she was the happiest mother on earth when she gave birth to twins in March 2017. But that euphoric feeling began to fade over the next few months, as she realized her son wasn't making the same developmental milestones as his sister. "I had a perfect benchmark because they were twins, and I saw that Maxwell was floppy—he didn't have muscle tone and couldn't hold his neck up," she recalls. At first doctors placated her with statements that boys sometimes develop slower than girls, but the difference was just too drastic. At 10 month old, Maxwell had never reached to grab a toy. In fact, he had never even used his hands.
Thinking that perhaps Maxwell couldn't see well, Freed took him to an ophthalmologist who was the first to confirm her worst fears. He didn't find Maxwell to have vision problems, but he thought there was something wrong with the boy's brain. He had seen similar cases before and they always turned out to be rare disorders, and always fatal. "Start preparing yourself for your child not to live," he had said.
Getting the diagnosis took months of painful, invasive procedures, as well as fighting with the health insurance to get the genetic testing approved. Finally, in June 2018, doctors at the Children's Hospital Colorado gave the Freeds their son's diagnosis—a genetic mutation so rare it didn't even have a name, just a bunch of letters jammed together into a word SLC6A1—same as the name of the mutated gene. The mutation, with only 40 cases known worldwide at the time, caused developmental disabilities, movement and speech disorders, and a debilitating form of epilepsy.
The doctors didn't know much about the disorder, but they said that Maxwell would also regress in his development when he turned three or four. They couldn't tell how long he would live. "Hopefully you would become an expert and educate us about it," they said, as they gave Freed a five-page paper on the SLC6A1 and told her to start calling scientists if she wanted to help her son in any way. When she Googled the name, nothing came up. She felt horrified. "Our disease was too rare to care."
Freed's husband, a 6'2'' college football player broke down in sobs and she realized that if anything could be done to help Maxwell, she'd have be the one to do it. "I understood that I had to fight like a mother," she says. "And a determined mother can do a lot of things."
The Freed family.
Courtesy Amber Freed
She quit her job as an equity analyst the day of the diagnosis and became a full-time SLC6A1 citizen scientist looking for researchers studying mutations of this gene. In the wee hours of the morning, she called scientists in Europe. As the day progressed, she called researchers on the East Coast, followed by the West in the afternoon. In the evening, she switched to Asia and Australia. She asked them the same question. "Can you help explain my gene and how do we fix it?"
Scientists need money to do research, so Freed launched Milestones for Maxwell fundraising campaign, and a SLC6A1 Connect patient advocacy nonprofit, dedicated to improving the lives of children and families battling this rare condition. And then it became clear that the mutation wasn't as rare as it seemed. As other parents began to discover her nonprofit, the number of known cases rose from 40 to 100, and later to 400, Freed says. "The disease is only rare until it messes with the wrong mother."
It took one mother to find another to start looking into what's happening inside Maxwell's brain. Freed came across Jeanne Paz, a Gladstone Institutes researcher who studies epilepsy with particular interest in absence or silent seizures—those that don't manifest by convulsions, but rather make patients absently stare into space—and that's one type of seizures Maxwell has. "It's like a brief period of silence in the brain during which the person doesn't pay attention to what's happening, and as soon as they come out of the seizure they are back to life," Paz explains. "It's like a pause button on consciousness." She was working to understand the underlying biology.
To understand how seizures begin, spread and stop, Paz uses optogenetics in mice. From words "genetic" and "optikós," which means visible in Greek, the optogenetics technique involves two steps. First, scientists introduce a light-sensitive gene into a specific brain cell type—for example into excitatory neurons that release glutamate, a neurotransmitter, which activates other cells in the brain. Then they implant a very thin optical fiber into the brain area where they forged these light-sensitive neurons. As they shine the light through the optical fiber, researchers can make excitatory neurons to release glutamate—or instead tell them to stop being active and "shut up". The ability to control what these neurons of interest do, quite literally sheds light onto where seizures start, how they propagate and what cells are involved in stopping them.
"Let's say a seizure started and we shine the light that reduces the activity of specific neurons," Paz explains. "If that stops the seizure, we know that activating those cells was necessary to maintain the seizure." Likewise, shutting down their activity will make the seizure stop.
Freed reached out to Paz in 2019 and the two women had an instant connection. They were both passionate about brain and seizures research, even if for different reasons. Freed asked Paz if she would study her son's seizures and Paz agreed.
To do that, Paz needed mice that carried the SLC6A1 mutation, so Freed found a company in China that created them to specs. The company replaced a mouse SLC6A1 gene with a human mutated one and shipped them over to Paz's lab. "We call them Maxwell mice," Paz says, "and we are now implanting electrodes into them to see which brain regions generate seizures." That would help them understand what goes wrong and what brain cells are malfunctioning in the SLC6A1 mice—and help scientists better understand what might cause seizures in children.
Bred to carry SLC6A1 mutation, these "Maxwell mice" will help better understand this debilitating genetic disease. (These mice are from Vanderbilt University, where researchers are also studying SLC6A1.)
Courtesy Amber Freed
This information—along with other research Amber is funding in other institutions—will inform the development of a novel genetic treatment, in which scientists would deploy a harmless virus to deliver a healthy, working copy of the SLC6A1 gene into the mice brains. They would likely deliver the therapeutic via a spinal tap infusion, and if it works and doesn't produce side effects in mice, the human trials will follow.
In the meantime, Freed is raising money to fund other research of various stop-gap measures. On April 22, 2021, she updated her Milestone for Maxwell page with a post that her nonprofit is funding yet another effort. It is a trial at Weill Cornell Medicine in New York City, in which doctors will use an already FDA-approved drug, which was recently repurposed for the SLC6A1 condition to treat epilepsy in these children. "It will buy us time," Freed says—while the gene therapy effort progresses.
Freed is determined to beat SLC6A1 before it beats down her family. She hopes to put an end to this disease—and similar genetic diseases—once and for all. Her goal is not only to have scientists create a remedy, but also to add the mutation to a newborn screening panel. That way, children born with this condition in the future would receive gene therapy before they even leave the hospital.
"I don't want there to be another Maxwell Freed," she says, "and that's why I am fighting like a mother." The gene therapy trial still might be a few years away, but the Weill Cornell one aims to launch very soon—possibly around Mother's Day. This is yet another milestone for Maxwell, another baby step forward—and the best gift a mother can get.
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.
This virtual event convened leading scientific and medical experts to address the public's questions and concerns about Covid-19 vaccines in kids and teens. Highlight video below.
DATE:
Thursday, May 13th, 2021
12:30 p.m. - 1:45 p.m. EDT
Dr. H. Dele Davies, M.D., MHCM
Senior Vice Chancellor for Academic Affairs and Dean for Graduate Studies at the University of Nebraska Medical (UNMC). He is an internationally recognized expert in pediatric infectious diseases and a leader in community health.
Dr. Emily Oster, Ph.D.
Professor of Economics at Brown University. She is a best-selling author and parenting guru who has pioneered a method of assessing school safety.
Dr. Tina Q. Tan, M.D.
Professor of Pediatrics at the Feinberg School of Medicine, Northwestern University. She has been involved in several vaccine survey studies that examine the awareness, acceptance, barriers and utilization of recommended preventative vaccines.
Dr. Inci Yildirim, M.D., Ph.D., M.Sc.
Associate Professor of Pediatrics (Infectious Disease); Medical Director, Transplant Infectious Diseases at Yale School of Medicine; Associate Professor of Global Health, Yale Institute for Global Health. She is an investigator for the multi-institutional COVID-19 Prevention Network's (CoVPN) Moderna mRNA-1273 clinical trial for children 6 months to 12 years of age.
About the Event Series
This event is the second of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
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Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.