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."
If you look back on the last century of scientific achievements, you might notice that most of the scientists we celebrate are overwhelmingly white, while scientists of color take a backseat. Since the Nobel Prize was introduced in 1901, for example, no black scientists have landed this prestigious award.
The work of black women scientists has gone unrecognized in particular. Their work uncredited and often stolen, black women have nevertheless contributed to some of the most important advancements of the last 100 years, from the polio vaccine to GPS.
Here are five black women who have changed science forever.
Dr. May Edward Chinn
Dr. May Edward Chinn practicing medicine in Harlem
George B. Davis, PhD.
Chinn was born to poor parents in New York City just before the start of the 20th century. Although she showed great promise as a pianist, playing with the legendary musician Paul Robeson throughout the 1920s, she decided to study medicine instead. Chinn, like other black doctors of the time, were barred from studying or practicing in New York hospitals. So Chinn formed a private practice and made house calls, sometimes operating in patients’ living rooms, using an ironing board as a makeshift operating table.
Chinn worked among the city’s poor, and in doing this, started to notice her patients had late-stage cancers that often had gone undetected or untreated for years. To learn more about cancer and its prevention, Chinn begged information off white doctors who were willing to share with her, and even accompanied her patients to other clinic appointments in the city, claiming to be the family physician. Chinn took this information and integrated it into her own practice, creating guidelines for early cancer detection that were revolutionary at the time—for instance, checking patient health histories, checking family histories, performing routine pap smears, and screening patients for cancer even before they showed symptoms. For years, Chinn was the only black female doctor working in Harlem, and she continued to work closely with the poor and advocate for early cancer screenings until she retired at age 81.
Alice Ball
Pictorial Press Ltd/Alamy
Alice Ball was a chemist best known for her groundbreaking work on the development of the “Ball Method,” the first successful treatment for those suffering from leprosy during the early 20th century.
In 1916, while she was an undergraduate student at the University of Hawaii, Ball studied the effects of Chaulmoogra oil in treating leprosy. This oil was a well-established therapy in Asian countries, but it had such a foul taste and led to such unpleasant side effects that many patients refused to take it.
So Ball developed a method to isolate and extract the active compounds from Chaulmoogra oil to create an injectable medicine. This marked a significant breakthrough in leprosy treatment and became the standard of care for several decades afterward.
Unfortunately, Ball died before she could publish her results, and credit for this discovery was given to another scientist. One of her colleagues, however, was able to properly credit her in a publication in 1922.
Henrietta Lacks
onathan Newton/The Washington Post/Getty
The person who arguably contributed the most to scientific research in the last century, surprisingly, wasn’t even a scientist. Henrietta Lacks was a tobacco farmer and mother of five children who lived in Maryland during the 1940s. In 1951, Lacks visited Johns Hopkins Hospital where doctors found a cancerous tumor on her cervix. Before treating the tumor, the doctor who examined Lacks clipped two small samples of tissue from Lacks’ cervix without her knowledge or consent—something unthinkable today thanks to informed consent practices, but commonplace back then.
As Lacks underwent treatment for her cancer, her tissue samples made their way to the desk of George Otto Gey, a cancer researcher at Johns Hopkins. He noticed that unlike the other cell cultures that came into his lab, Lacks’ cells grew and multiplied instead of dying out. Lacks’ cells were “immortal,” meaning that because of a genetic defect, they were able to reproduce indefinitely as long as certain conditions were kept stable inside the lab.
Gey started shipping Lacks’ cells to other researchers across the globe, and scientists were thrilled to have an unlimited amount of sturdy human cells with which to experiment. Long after Lacks died of cervical cancer in 1951, her cells continued to multiply and scientists continued to use them to develop cancer treatments, to learn more about HIV/AIDS, to pioneer fertility treatments like in vitro fertilization, and to develop the polio vaccine. To this day, Lacks’ cells have saved an estimated 10 million lives, and her family is beginning to get the compensation and recognition that Henrietta deserved.
Dr. Gladys West
Andre West
Gladys West was a mathematician who helped invent something nearly everyone uses today. West started her career in the 1950s at the Naval Surface Warfare Center Dahlgren Division in Virginia, and took data from satellites to create a mathematical model of the Earth’s shape and gravitational field. This important work would lay the groundwork for the technology that would later become the Global Positioning System, or GPS. West’s work was not widely recognized until she was honored by the US Air Force in 2018.
Dr. Kizzmekia "Kizzy" Corbett
TIME Magazine
At just 35 years old, immunologist Kizzmekia “Kizzy” Corbett has already made history. A viral immunologist by training, Corbett studied coronaviruses at the National Institutes of Health (NIH) and researched possible vaccines for coronaviruses such as SARS (Severe Acute Respiratory Syndrome) and MERS (Middle East Respiratory Syndrome).
At the start of the COVID pandemic, Corbett and her team at the NIH partnered with pharmaceutical giant Moderna to develop an mRNA-based vaccine against the virus. Corbett’s previous work with mRNA and coronaviruses was vital in developing the vaccine, which became one of the first to be authorized for emergency use in the United States. The vaccine, along with others, is responsible for saving an estimated 14 million lives.On today’s episode of Making Sense of Science, I’m honored to be joined by Dr. Paul Song, a physician, oncologist, progressive activist and biotech chief medical officer. Through his company, NKGen Biotech, Dr. Song is leveraging the power of patients’ own immune systems by supercharging the body’s natural killer cells to make new treatments for Alzheimer’s and cancer.
Whereas other treatments for Alzheimer’s focus directly on reducing the build-up of proteins in the brain such as amyloid and tau in patients will mild cognitive impairment, NKGen is seeking to help patients that much of the rest of the medical community has written off as hopeless cases, those with late stage Alzheimer’s. And in small studies, NKGen has shown remarkable results, even improvement in the symptoms of people with these very progressed forms of Alzheimer’s, above and beyond slowing down the disease.
In the realm of cancer, Dr. Song is similarly setting his sights on another group of patients for whom treatment options are few and far between: people with solid tumors. Whereas some gradual progress has been made in treating blood cancers such as certain leukemias in past few decades, solid tumors have been even more of a challenge. But Dr. Song’s approach of using natural killer cells to treat solid tumors is promising. You may have heard of CAR-T, which uses genetic engineering to introduce cells into the body that have a particular function to help treat a disease. NKGen focuses on other means to enhance the 40 plus receptors of natural killer cells, making them more receptive and sensitive to picking out cancer cells.
Paul Y. Song, MD is currently CEO and Vice Chairman of NKGen Biotech. Dr. Song’s last clinical role was Asst. Professor at the Samuel Oschin Cancer Center at Cedars Sinai Medical Center.
Dr. Song served as the very first visiting fellow on healthcare policy in the California Department of Insurance in 2013. He is currently on the advisory board of the Pritzker School of Molecular Engineering at the University of Chicago and a board member of Mercy Corps, The Center for Health and Democracy, and Gideon’s Promise.
Dr. Song graduated with honors from the University of Chicago and received his MD from George Washington University. He completed his residency in radiation oncology at the University of Chicago where he served as Chief Resident and did a brachytherapy fellowship at the Institute Gustave Roussy in Villejuif, France. He was also awarded an ASTRO research fellowship in 1995 for his research in radiation inducible gene therapy.
With Dr. Song’s leadership, NKGen Biotech’s work on natural killer cells represents cutting-edge science leading to key findings and important pieces of the puzzle for treating two of humanity’s most intractable diseases.
Show links
- Paul Song LinkedIn
- NKGen Biotech on Twitter - @NKGenBiotech
- NKGen Website: https://nkgenbiotech.com/
- NKGen appoints Paul Song
- Patient Story: https://pix11.com/news/local-news/long-island/promising-new-treatment-for-advanced-alzheimers-patients/
- FDA Clearance: https://nkgenbiotech.com/nkgen-biotech-receives-ind-clearance-from-fda-for-snk02-allogeneic-natural-killer-cell-therapy-for-solid-tumors/Q3 earnings data: https://www.nasdaq.com/press-release/nkgen-biotech-inc.-reports-third-quarter-2023-financial-results-and-business