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."
"Making Sense of Science" is a monthly podcast that features interviews with leading medical and scientific experts about the latest developments and the big ethical and societal questions they raise. This episode is hosted by science and biotech journalist Emily Mullin, summer editor of the award-winning science outlet Leaps.org.
Listen to the episode:
Meet the Psychologist Using Psychedelics to Treat Racial Trauma
Monnica Williams was stuck. The veteran psychologist wanted to conduct a study using psychedelics, but her university told her they didn't have the expertise to evaluate it via an institutional review board, which is responsible for providing ethical and regulatory oversight for research that involves human participants. Instead, they directed her to a hospital, whose reviewers turned it down, citing research of a banned substance as unethical.
"I said, 'We're not using illegal psilocybin, we're going through Health Canada,'" Williams said. Psilocybin was banned in Canada in 1974, but can now be obtained with an exemption from Health Canada, the federal government's health policy department. After learning this, the hospital review board told Williams they couldn't review her proposal because she's not affiliated with the hospital, after all.
It's all part of balancing bureaucracy with research goals for Williams, a leading expert on racial trauma and psychedelic medicine, as well as obsessive compulsive disorder (OCD), at the University of Ottawa. She's exploring the use of hallucinogenic substances like MDMA and psilocybin — commonly known as ecstasy and magic mushrooms, respectively — to help people of color address the psychological impacts of systemic racism. A prolific researcher, Williams also works as an expert witness, offering clinical evaluations for racial trauma cases.
Scientists have long known that psychedelics produce an altered state of consciousness and openness to new perspectives. For people with mental health conditions who haven't benefited from traditional therapy, psychedelics may be able to help them discover what's causing their pain or trauma, including racial trauma—the mental and emotional injury spurred by racial bias.
"Using psychedelics can not only bring these pain points to the surface for healing, but can reduce the anxiety or response to these memories and allow them to speak openly about them without the pain they bring," Williams says. Her research harnesses the potential of psychedelics to increase neuroplasticity, which includes the brain's ability to build new pathways.
"People of color are dealing with racism all the time, in large and small ways, and even dealing with racism in healthcare, even dealing with racism in therapy."
But she says therapists of color aren't automatically equipped to treat racial trauma. First, she notes, people of color are "vastly underrepresented in the mental health workforce." This is doubly true in psychedelic-assisted psychotherapy, in which a person is guided through a psychedelic session by a therapist or team of therapists, then processes the experience in subsequent therapy sessions.
"On top of that, the therapists of color are getting the same training that the white therapists are getting, so it's not even really guaranteed that they're going to be any better at helping a person that may have racial trauma emerging as part of their experience," she says.
In her own training to become a clinical psychologist at the University of Virginia, Williams says she was taught "how to be a great psychologist for white people." Yet even people of color, she argues, need specialized training to work with marginalized groups, particularly when it comes to MDMA, psilocybin and other psychedelics. Because these drugs can lower natural psychological defense mechanisms, Williams says, it's important for providers to be specially trained.
"People of color are dealing with racism all the time, in large and small ways, and even dealing with racism in healthcare, even dealing with racism in therapy. So [they] generally develop a lot of defenses and coping strategies to ward off racism so that they can function." she says. This is particularly true with psychedelic-assisted psychotherapy: "One possibility is that you're going to be stripped of your defenses, you're going to be vulnerable. And so you have to work with a therapist who is going to understand that and not enact more racism in their work with you."
Williams has struggled to find funding and institutional approval for research involving psychedelics, or funding for investigations into racial trauma or the impacts of conditions like OCD and post-traumatic stress disorder (PTSD) in people of color. With the bulk of her work focusing on OCD, she hoped to focus on people of color, but found there was little funding for that type of research. In 2020, that started to change as structural racism garnered more media attention.
After the killing of George Floyd, a 46-year-old Black man, by a white police officer in May 2020, Williams was flooded with media requests. "Usually, when something like that happens, I get contacted a lot for a couple of weeks, and it dies off. But after George Floyd, it just never did."
Monnica Williams, clinical psychologist at the University of Ottawa
Williams was no stranger to the questions that soon blazed across headlines: How can we mitigate microaggressions? How do race and ethnicity impact mental health? What terms should we use to discuss racial issues? What constitutes an ally, and why aren't there more of them? Why aren't there more people of color in academia, and so many other fields?
Now, she's hoping that the increased attention on racial justice will mean more acceptance for the kind of research she's doing.
In fact, Williams herself has used psychedelics in order to gain a better understanding of how to use them to treat racial trauma. In a study published in January, she and two other Black female psychotherapists took MDMA in a supervised setting, guided by a team of mental health practitioners who helped them process issues that came up as the session progressed. Williams, who was also the study's lead author, found that participants' experiences centered around processing and finding release from racial identities, and, in one case, of simply feeling wholly human without the burden of racial identity for the first time.
The purpose of the study was twofold: to understand how Black women react to psychedelics and to provide safe, firsthand, psychedelic experiences to Black mental health practitioners. One of the other study participants has since gone on to offer psychedelic-assisted psychotherapy to her own patients.
Psychedelic research, and psilocybin in particular, has become a hot topic of late, particularly after Oregon became the first state to legalize it for therapeutic use last November. A survey-based, observational study with 313 participants, published in 2020, paved the way for Williams' more recent MDMA experiments by describing improvements in depression, anxiety and racial trauma among people of color who had used LSD, psilocybin or MDMA in a non-research setting.
Williams and her team included only respondents who reported a moderate to strong psychoactive effect of past psychedelic consumption and believed these experiences provided "relief from the challenging effects of ethnic discrimination." Participants reported a memorable psychedelic experience as well as its acute and lasting effects, completing assessments of psychological insight, mystical experience and emotional challenges experienced during psychedelic experience, then describing their mental health — including depression, anxiety and trauma symptoms — before and after that experience.
Still, Williams says addressing racism is much more complex than treating racial trauma. "One of the questions I get asked a lot is, 'How can Black people cope with racism?' And I don't really like that question," she says. "I think it's important and I don't mind answering it, but I think the more important question is, how can we end racism? What can Black people do to stop racism that's happening to them and what can we do as a society to stop racism? And people aren't really asking this question."