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."
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers
The Toxic Effects of Noise and What We’re Not Doing About It
Erica Walker had a studio in her Brookline, Mass. apartment where she worked as a bookbinder and furniture maker. That was until a family with two rowdy children moved in above her.
The kids ran amuck, disrupting her sleep and work. Ear plugs weren’t enough to blot out the commotion. Aside from anger and a sense of lost control, the noise increased her heart rate and made her stomach feel like it was dropping, she says.
That’s when Walker realized that noise is a public health problem, not merely an annoyance. She set up her own “mini study” on how the clamor was affecting her. She monitored sound levels in her apartment and sent saliva samples to a lab to measure her stress levels.
Walker ultimately sold her craft equipment and returned to school to study public health. Today she is assistant professor of epidemiology and director of the Community Noise Lab at the Brown University School of Public Health. “We treat noise like a first world problem—like a sacrifice we should have to make for modern conveniences. But it’s a serious environmental stressor,” she asserts.
Our daily soundscape is a cacophony of earsplitting jets, motorcycles, crying babies, construction sites or gunshots if you’re in the military. Noise exposure is the primary cause of preventable hearing loss. Researchers have identified links between excessive noise and a heightened risk of heart disease, metabolic disorders, anxiety, depression, sleep disorders, and impaired cognition. Even wildlife suffers. Blasting oil drills and loud shipping vessels impede the breeding, feeding and migration of whales and dolphins.
At one time, the federal government had our back… and our ears. Congress passed the Noise Control Act in 1972. The Environmental Protection Agency set up the Office of Noise Abatement and Control (ONAC) to launch research, explore solutions and establish noise emission standards. But ONAC was defunded in 1981 amidst a swirl of antiregulatory sentiment.
Impossibly Loud and Unhealthy
Daniel Fink. a physician, WHO consultant, and board chair of The Quiet Coalition, a program of the nonprofit Quiet Communities, likens the effect of noise to the invisible but cumulative harm of second-hand smoke. About 1 in 4 adults in the U.S. who report excellent to good hearing already have some hearing loss. The injury can happen after one loud concert or from years with a blaring TV. Some people are more genetically susceptible to noise-related hearing loss than others.
“People say noise isn’t a big deal but it bothers your body whether you realize it or not,” says Ted Rueter, director of Noise Free America: A Coalition to Promote Quiet. Noise can chip away at your ears or cardiovascular system even while you’re sleeping. Rueter became a “quiet advocate” while a professor at UCLA two decades ago. He was plagued by headaches, fatigue and sleep deprivation caused by the hubbub of Los Angeles, he says.
The louder a sound is, and the longer you are exposed to it, the more likely it will cause nerve damage and harmful fluid buildup in your inner ear. Normal speech is 50-60 decibels (dBs). The EPA recommends that 24-hour exposure to noise should be no higher than 70 weighted decibels over 24 hours (weighted to approximate how the human ear perceives the sound) to prevent hearing loss but a 55 dB limit is recommended to protect against other harms from noise, too.
The decibel scale is logarithmic. That means 80 dB is 10 times louder than 70 dB. Trucks and motorcycles run 90 dBs. A gas-powered leaf blower, jackhammer or snow blower will cost you 100 dBs. A rock concert is in the 110 dB range. Aircraft takeoffs or sirens? 120 dBs.
Walker, the Brown professor, says that sound measurements often use misleading metrics, though, because they don’t include low frequency sound that disturb the body. The high frequency of a screeching bus will register in decibels but the sound that makes your chest reverberate is not accounted for, she explains. ‘How loud?’ is a superficial take when it comes to noise, Walker says.
After realizing the impact of noise on her own health, Erica Walker was inspired to change careers and become director of the Community Noise Lab at the Brown University School of Public Health.
Erica Walker
Fink adds that the extent to which noise impairs hearing is underestimated. People assume hearing loss is due to age but it’s not inevitable, he says. He cites studies of older people living in quiet, isolated areas who maintain excellent hearing. Just like you can prevent wrinkles by using sunscreen, you can preserve hearing by using ear plugs when attending fireworks or hockey games.
You can enable push notifications on a Smart Watch to alert you at a bar exceeding healthy sound levels. Free apps like SoundPrint, iHEARu, or NoiseTube can do decibel checks, too, but you don’t need one, says Fink. “If you can’t carry a conversation at normal volume, it’s too loud and your auditory health is at risk,” he says.
About 40 million U.S. adults, ages 20-69, have noise-induced hearing loss. Fink is among them after experiencing tinnitus (ringing or buzzing in the ears) on leaving a raucous New Year’s Eve party in 2007. The condition is permanent and he wears earplugs now for protection.
Fewer are aware of the link between noise pollution and heart disease. Piercing noise is stressful, raising blood pressure and heart rate. If you live near a freeway or constantly barking dog, the chronic sound stress can trigger systemic inflammation and the vascular changes associated with heart attacks and stroke.
Researchers at Rutgers University’s Robert Wood Johnson Medical School, working with data from the state’s Bureau of Transportation, determined that 1 in 20 heart attacks in New Jersey during 2018 were due to noise from highways, trains and air traffic. That’s 800 heart attack hospitalizations in the state that year.
Another study showed that incidence of hypertension and hardening arteries decreased during the Covid-19 air lockdown among Poles in Krakow routinely exposed to aircraft noise. The authors, comparing their pre-pandemic 2015 results to 2020 data, concluded it was no coincidence.
Mental health takes a hit, too. Chronic noise can provoke anxiety, depression and violence. Cognitively, there is ample evidence that noise disturbance lowers student achievement and worker productivity, and hearing loss among older people can speed up cognitive decline.
Noise also contributes to health disparities. People in neighborhoods with low socioeconomic status and a higher percentage of minority residents bear the brunt of noise. Affluent people have the means to live far from airports, factories, and honking traffic.
Out, Out, Damn Noise
Europe is ahead of the U.S. in tackling noise pollution. The World Health Organization developed policy guidelines used by the European Environment Agency to establish noise regulations and standards, and progress reports are issued.
Americans are relying too much on personal protective equipment (PPE) instead of eliminating or controlling noise. The Centers of Disease Control and Prevention rank PPE as the least useful response. Earplugs and muffs are effective, says Walker, but these devices are “a band-aid on a waterfall.”
Editing out noise during product design is the goal. Engineers have an arsenal of techniques and know-how for that. The problem is that these solutions aren’t being applied.
A better way to lower the volume is by maintaining or substituting equipment intended for common use. Piercing building alarms can be replaced with visual signals that flash alerts. Clanking chain and gear drives can be swapped out with belt drives. Acoustical barriers can wall off highway noise. Hospitals can soften beeping monitors and limit loudspeaker blasts. Double paned windows preserve quiet.
Editing out noise during product design is the goal. Engineers have an arsenal of techniques and know-how for that. The problem is that these solutions aren’t being applied, says Jim Thompson, an engineer and editor of the Noise Control Engineering Journal, published by the Institute of Noise Control Engineering of the USA
Engineers have materials to insulate, absorb, reflect, block, seal or diffuse noise. Building walls can be padded. Metal gears and parts can be replaced with plastic. Clattering equipment wheels can be rubberized. In recent years, building certifications such as LEED have put more emphasis on designs that minimize harmful noise.
Walker faults urban planners, too. A city’s narrow streets and taller buildings create a canyon effect which intensifies noise. City planners could use bypasses, rerouting, and other infrastructure strategies to pump down traffic volume. Sound-absorbing asphalt pavement exists, too.
Some municipalities are taking innovative measures on their own. Noise cameras have been installed in Knoxville, Miami and New York City this year and six California cities will join suit next year. If your muffler or audio system registers 86 dB or higher, you may receive a warning, fine or citation, similar to how a red-light camera works. Rueter predicts these cameras will become commonplace.
Based on understanding how metabolic processes affect noise-induced hearing loss in animal models, scientists are exploring whether pharmacological interventions might work to inhibit cellular damage or improve cellular defenses against noise.
Washington, DC, and the University of Southern California have banned gas-powered leaf blowers in lieu of quieter battery-powered models to reduce both noise and air pollution. California will be the first state to ban the sale of gas-powered lawn equipment starting 2024.
New York state legislators enacted the SLEEP (Stop Loud and Excessive Exhaust Pollution) Act in 2021. This measure increases enforcement and fines against motorists and repair shops that illegally modify mufflers and exhaust systems for effect.
“A lot more basic science and application research is needed [to control noise],” says Thompson, noting that funding for this largely dried up after the 1970s. Based on understanding how metabolic processes affect noise-induced hearing loss in animal models, scientists are exploring whether pharmacological interventions might work to inhibit cellular damage or improve cellular defenses against noise.
Studying biochemical or known genetic markers for noise risk could lead to other methods for preventing hearing loss. This would offer an opportunity to identify people with significant risk so those more susceptible to hearing loss could start taking precautions to avoid noise or protect their ears in childhood.
These efforts could become more pressing in the near future, with the anticipated onslaught of drones, rising needs for air conditioners, and urban sprawl boding poorly for the soundscape. This, as deforestation destroys natural carbon absorption reservoirs and removes sound-buffering trees.
“Local and state governments don’t have a plan to deal with [noise] now or in the future,” says Walker. “We need to think about this with intentionality.”