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."
Gene Transfer Leads to Longer Life and Healthspan
In August, a study provided the first proof-of-principle that genetic material transferred from one species to another can increase both longevity and healthspan in the recipient animal.
The naked mole rat won’t win any beauty contests, but it could possibly win in the talent category. Its superpower: fighting the aging process to live several times longer than other animals its size, in a state of youthful vigor.
It’s believed that naked mole rats experience all the normal processes of wear and tear over their lifespan, but that they’re exceptionally good at repairing the damage from oxygen free radicals and the DNA errors that accumulate over time. Even though they possess genes that make them vulnerable to cancer, they rarely develop the disease, or any other age-related disease, for that matter. Naked mole rats are known to live for over 40 years without any signs of aging, whereas mice live on average about two years and are highly prone to cancer.
Now, these remarkable animals may be able to share their superpower with other species. In August, a study provided what may be the first proof-of-principle that genetic material transferred from one species can increase both longevity and healthspan in a recipient animal.
There are several theories to explain the naked mole rat’s longevity, but the one explored in the study, published in Nature, is based on the abundance of large-molecule high-molecular mass hyaluronic acid (HMM-HA).
A small molecule version of hyaluronic acid is commonly added to skin moisturizers and cosmetics that are marketed as ways to keep skin youthful, but this version, just applied to the skin, won’t have a dramatic anti-aging effect. The naked mole rat has an abundance of the much-larger molecule, HMM-HA, in the chemical-rich solution between cells throughout its body. But does the HMM-HA actually govern the extraordinary longevity and healthspan of the naked mole rat?
To answer this question, Dr. Vera Gorbunova, a professor of biology and oncology at the University of Rochester, and her team created a mouse model containing the naked mole rat gene hyaluronic acid synthase 2, or nmrHas2. It turned out that the mice receiving this gene during their early developmental stage also expressed HMM-HA.
The researchers found that the effects of the HMM-HA molecule in the mice were marked and diverse, exceeding the expectations of the study’s co-authors. High-molecular mass hyaluronic acid was more abundant in kidneys, muscles and other organs of the Has2 mice compared to control mice.
In addition, the altered mice had a much lower incidence of cancer. Seventy percent of the control mice eventually developed cancer, compared to only 57 percent of the altered mice, even after several techniques were used to induce the disease. The biggest difference occurred in the oldest mice, where the cancer incidence for the Has2 mice and the controls was 47 percent and 83 percent, respectively.
With regard to longevity, Has2 males increased their lifespan by more than 16 percent and the females added 9 percent. “Somehow the effect is much more pronounced in male mice, and we don’t have a perfect answer as to why,” says Dr. Gorbunova. Another improvement was in the healthspan of the altered mice: the number of years they spent in a state of relative youth. There’s a frailty index for mice, which includes body weight, mobility, grip strength, vision and hearing, in addition to overall conditions such as the health of the coat and body temperature. The Has2 mice scored lower in frailty than the controls by all measures. They also performed better in tests of locomotion and coordination, and in bone density.
Gorbunova’s results show that a gene artificially transferred from one species can have a beneficial effect on another species for longevity, something that had never been demonstrated before. This finding is “quite spectacular,” said Steven Austad, a biologist at the University of Alabama at Birmingham, who was not involved in the study.
Just as in lifespan, the effects in various organs and systems varied between the sexes, a common occurrence in longevity research, according to Austad, who authored the book Methuselah’s Zoo and specializes in the biological differences between species. “We have ten drugs that we can give to mice to make them live longer,” he says, “and all of them work better in one sex than in the other.” This suggests that more attention needs to be paid to the different effects of anti-aging strategies between the sexes, as well as gender differences in healthspan.
According to the study authors, the HMM-HA molecule delivered these benefits by reducing inflammation and senescence (cell dysfunction and death). The molecule also caused a variety of other benefits, including an upregulation of genes involved in the function of mitochondria, the powerhouses of the cells. These mechanisms are implicated in the aging process, and in human disease. In humans, virtually all noncommunicable diseases entail an acceleration of the aging process.
So, would the gene that creates HMM-HA have similar benefits for longevity in humans? “We think about these questions a lot,” Gorbunova says. “It’s been done by injections in certain patients, but it has a local effect in the treatment of organs affected by disease,” which could offer some benefits, she added.
“Mice are very short-lived and cancer-prone, and the effects are small,” says Steven Austad, a biologist at the University of Alabama at Birmingham. “But they did live longer and stay healthy longer, which is remarkable.”
As for a gene therapy to introduce the nmrHas2 gene into humans to obtain a global result, she’s skeptical because of the complexity involved. Gorbunova notes that there are potential dangers in introducing an animal gene into humans, such as immune responses or allergic reactions.
Austad is equally cautious about a gene therapy. “What this study says is that you can take something a species does well and transfer at least some of that into a new species. It opens up the way, but you may need to transfer six or eight or ten genes into a human” to get the large effect desired. Humans are much more complex and contain many more genes than mice, and all systems in a biological organism are intricately connected. One naked mole rat gene may not make a big difference when it interacts with human genes, metabolism and physiology.
Still, Austad thinks the possibilities are tantalizing. “Mice are very short-lived and cancer-prone, and the effects are small,” he says. “But they did live longer and stay healthy longer, which is remarkable.”
As for further research, says Austad, “The first place to look is the skin” to see if the nmrHas2 gene and the HMM-HA it produces can reduce the chance of cancer. Austad added that it would be straightforward to use the gene to try to prevent cancer in skin cells in a dish to see if it prevents cancer. It would not be hard to do. “We don’t know of any downsides to hyaluronic acid in skin, because it’s already used in skin products, and you could look at this fairly quickly.”
“Aging mechanisms evolved over a long time,” says Gorbunova, “so in aging there are multiple mechanisms working together that affect each other.” All of these processes could play a part and almost certainly differ from one species to the next.
“HMM-HA molecules are large, but we’re now looking for a small-molecule drug that would slow it’s breakdown,” she says. “And we’re looking for inhibitors, now being tested in mice, that would hinder the breakdown of hyaluronic acid.” Gorbunova has found a natural, plant-based product that acts as an inhibitor and could potentially be taken as a supplement. Ultimately, though, she thinks that drug development will be the safest and most effective approach to delivering HMM-HA for anti-aging.
A new study provides key insights in what causes Alzheimer's: a breakdown in the brain’s system for clearing waste.
In recent years, researchers of Alzheimer’s have made progress in figuring out the complex factors that lead to the disease. Yet, the root cause, or causes, of Alzheimer’s are still pretty much a mystery.
In fact, many people get Alzheimer’s even though they lack the gene variant we know can play a role in the disease. This is a critical knowledge gap for research to address because the vast majority of Alzheimer’s patients don’t have this variant.
A new study provides key insights into what’s causing the disease. The research, published in Nature Communications, points to a breakdown over time in the brain’s system for clearing waste, an issue that seems to happen in some people as they get older.
Michael Glickman, a biologist at Technion – Israel Institute of Technology, helped lead this research. I asked him to tell me about his approach to studying how this breakdown occurs in the brain, and how he tested a treatment that has potential to fix the problem at its earliest stages.
Dr. Michael Glickman is internationally renowned for his research on the ubiquitin-proteasome system (UPS), the brain's system for clearing the waste that is involved in diseases such as Huntington's, Alzheimer's, and Parkinson's. He is the head of the Lab for Protein Characterization in the Faculty of Biology at the Technion – Israel Institute of Technology. In the lab, Michael and his team focus on protein recycling and the ubiquitin-proteasome system, which protects against serious diseases like Alzheimer’s, Parkinson’s, cystic fibrosis, and diabetes. After earning his PhD at the University of California at Berkeley in 1994, Michael joined the Technion as a Senior Lecturer in 1998 and has served as a full professor since 2009.
Dr. Michael Glickman