The Algorithm Will See You Now

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.

(© Tex vector/Adobe)



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."

Eve Herold
Eve Herold is an award-winning science writer and consultant in the scientific and medical nonprofit space. A longtime communications and policy executive for scientific organizations, she currently serves as Director of Policy Research and Education for the Healthspan Action Coalition. She has written extensively about issues at the crossroads of science and society, including regenerative medicine, aging and longevity, medical implants, transhumanism, robotics and AI, and bioethical issues in leading-edge medicine. Her books include Stem Cell Wars and Beyond Human, and her latest book, Robots and the People Who Love Them, will be released in January 2024. Her work has appeared in Vice, Medium, The Washington Post and the Boston Globe, among others. She’s a frequent contributor to Leaps.org and is the recipient of the 2019 Arlene Eisenberg Award from the American Society of Journalists and Authors.
Six Questions about the Kids' COVID Vaccine, Answered by an Infectious Disease Doctor

The author, an infectious disease physician, pictured with his two daughters who are getting vaccinated against COVID-19.

Courtesy of Chin-Hong

I enthusiastically support the vaccination against COVID for children aged 5-11 years old. As an infectious disease doctor who took care of hundreds of COVID-19 patients over the past 20 months, I have seen the immediate and long-term consequences of COVID-19 on patients – and on their families. As a father of two daughters, I have lived through the fear and anxiety of protecting my kids at all cost from the scourges of the pandemic and worried constantly about bringing the virus home from work.

It is imperative that we vaccinate as many children in the community as possible. There are several reasons why. First children do get sick from COVID-19. Over the course of the pandemic in the U.S, more than 2 million children aged 5-11 have become infected, more than 8000 have been hospitalized, and more than 100 have died, making COVID one of the top 10 causes of pediatric deaths in this age group over the past year. Children are also susceptible to chronic consequences of COVID such as long COVID and multisystem inflammatory syndrome in children (MIS-C). Most studies demonstrate that 10-30% of children will develop chronic symptoms following COVID-19. These include complaints of brain fog, fatigue, trouble breathing, fever, headache, muscle and joint pains, abdominal pain, mood swings and even psychiatric disorders. Symptoms typically last from 4-8 weeks in children, with some reporting symptoms that persist for many months.

Keep Reading Keep Reading
Peter Chin-Hong
Dr. Peter Chin-Hong is Associate Dean for Regional Campuses and professor of medicine at UCSF School of Medicine. He is a medical educator who specializes in treating infectious diseases, particularly infections that develop in patients who have suppressed immune systems, such as solid organ and hematopoietic stem cell transplant recipients and HIV+ organ transplant recipients. He directs the immunocompromised host infectious diseases program at UCSF. His research focuses on donor derived infections in transplant recipients and molecular diagnostics of infectious diseases in patients with suppressed immune systems. He earned his undergraduate and medical degrees from Brown University, before completing an internal medicine residency and infectious diseases fellowship at UCSF, where he is Professor of Medicine and Director of the Yearlong Inquiry Program in the School of Medicine. He was the inaugural holder of the Academy of Medical Educators Endowed Chair for Innovation in Teaching.
Food Poisoning Sickens Millions a Year. Now, a Surprising Weapon Is Helping Protect Against Contamination.

Phages, which are harmless viruses that destroy specific bacteria, are becoming useful tools to protect our food supply.

Every year, one in seven people in America comes down with a foodborne illness, typically caused by a bacterial pathogen, including E.Coli, listeria, salmonella, or campylobacter. That adds up to 48 million people, of which 120,000 are hospitalized and 3000 die, according to the Centers for Disease Control. And the variety of foods that can be contaminated with bacterial pathogens is growing too. In the 20th century, E.Coli and listeria lurked primarily within meat. Now they find their way into lettuce, spinach, and other leafy greens, causing periodic consumer scares and product recalls. Onions are the most recent suspected culprit of a nationwide salmonella outbreak.

Some of these incidents are almost inevitable because of how Mother Nature works, explains Divya Jaroni, associate professor of animal and food sciences at Oklahoma State University. These common foodborne pathogens come from the cattle's intestines when the animals shed them in their manure—and then they get washed into rivers and lakes, especially in heavy rains. When this water is later used to irrigate produce farms, the bugs end up on salad greens. Plus, many small farms do both—herd cattle and grow produce.

"Unfortunately for us, these pathogens are part of the microflora of the cows' intestinal tract," Jaroni says. "Some farmers may have an acre or two of cattle pastures, and an acre of a produce farm nearby, so it's easy for this water to contaminate the crops."

Keep Reading Keep Reading
Lina Zeldovich

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.