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."
CandyCodes could provide sweet justice against fake pills
When we swallow a pill, we hope it will work without side effects. Few of us know to worry about a growing issue facing the pharmaceutical industry: counterfeit medications. These pills, patches, and other medical products might look just like the real thing. But they’re often stuffed with fillers that dilute the medication’s potency or they’re simply substituted for lookalikes that contain none of the prescribed medication at all.
Now, bioengineer William Grover at the University of California, Riverside, may have a solution. Inspired by the tiny, multi-colored sprinkles called nonpareils that decorate baked goods and candies, Grover created CandyCodes pill coatings to prevent counterfeits.
The idea was borne out of pandemic boredom. Confined to his home, Grover was struck by the patterns of nonpareils he saw on candies, and found himself counting the number of little balls on each one. “It’s random, how they’re applied,” he says. “I wondered if it ever repeats itself or if each of these candies is unique in the entire world.” He suspected the latter, and some quick math proved his hypothesis: Given dozens of nonpareils per candy in a handful of different colors, it’s highly unlikely that the sprinklings on any two candies would be identical.
He quickly realized his finding could have practical applications: pills or capsules could be coated with similar “sprinkles,” with the manufacturer photographing each pill or capsule before selling its products. Consumers looking to weed out fakes could potentially take a photo with their cell phones and go online to compare images of their own pills to the manufacturer’s database, with the help of an algorithm that would determine their authenticity. Or, a computer could generate another type of unique identifier, such as a text-based code, tracking to the color and location of the sprinkles. This would allow for a speedier validation than a photo-based comparison, Grover says. “It could be done very quickly, in a fraction of a second.”
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes. But such methods, while functional, can be costly to implement, Grover says.
It wouldn’t be paranoid to take such precautions. Counterfeits are a growing problem, according to Young Kim, a biomedical engineer at Purdue University who was not involved in the CandyCodes study. “There are approximately 40,000 online pharmacies that one can access via the Internet,” he says. “Only three to four percent of them are operated legally.” Purchases from online pharmacies rose dramatically during the pandemic, and Kim expects a boom in counterfeit medical products alongside it.
The FDA warns that U.S. consumers can be exposed to counterfeits through online purchases, in particular. The problem is magnified in low- to middle-income nations, where one in 10 medical products are counterfeit, according to a World Health Organization estimate. Cost doesn’t seem to be a factor, either; antimalarials and antibiotics are most often reported as counterfeits or fakes, and generic medications are swapped as often as brand-name drugs, according to the same WHO report.
Counterfeits weren’t tracked globally until 2013; since then, there have been 1,500 reports to the WHO, with actual incidences of counterfeiting likely much higher. Fake medicines have been estimated to result in costs of $200 billion each year, and are blamed for more than 72,000 pneumonia- and 116,000 malaria-related deaths.
Researchers and manufacturers have already developed some anti-counterfeit tools, including built-in identifiers like edible papers with scannable QR codes or barcodes that are stamped onto or otherwise incorporated into pills and other medical products. But such methods, while functional, can be costly to implement, Grover says.
CandyCodes could provide unique identifiers for at least 41 million pills for every person on the planet.
William Grover
“Putting universal codes on each pill and each dosage is attractive,” he says. “The challenge is, how can we do it in a way that requires as little modification to the existing manufacturing process as possible? That's where I hope CandyCodes have an edge. It's not zero modification, but I hope it is as minor a modification of the manufacturing process as possible.”
Kim calls the concept “a clever idea to introduce entropy for high-level security” even if it may not be as close to market as other emerging technologies, including some edible watermarks he’s helped develop. He points out that CandyCodes still needs to be tested for reproducibility and readability.
The possibilities are already intriguing, though. Grover’s recent research, published in Scientific Reports, predicts that unique codes could be used for at least 41 million pills for every person on the planet.
Sadly, CandyCodes’ multicolored bits probably won’t taste like candy. They must be made of non-caloric ingredients to meet the international regulatory standards that govern food dyes and colorants. But Grover hopes CandyCodes represent a simple, accessible solution to a heart-wrenching issue. “This feels like trying to track down and go after bad guys,” he says. “Someone who would pass off a medicine intended for a child or a sick person and pass it off as something effective, I can't imagine anything much more evil than that. It's fun and, and a little fulfilling to try to develop technologies that chip away at that.”
Waste smothering our oceans is worth billions – here’s what we can do with all that sh$t
There’s hardly a person out there who hasn’t heard of the Great Pacific Garbage Patch. That type of pollution is impossible to miss. It stares you in the face from pictures and videos of sea turtles with drinking straws up their noses and acres of plastic swirling in the sea.
It demands you to solve the problem—and it works. The campaign to raise awareness about plastic pollution in the oceans has resulted in new policies, including bans on microplastics in personal care products, technology to clean up the plastic, and even new plastic-like materials that are better for the environment.
But there’s a different type of pollution smothering the ocean as you read this. Unfortunately, this one is almost invisible, but no less damaging. In fact, it’s even more serious than plastic and most people have no idea it even exists. It is literally under our noses, destroying our oceans, lakes, and rivers – and yet we are missing it completely while contributing to it daily. In fact, we exacerbate it multiple times a day—every time we use the bathroom.
It is the way we do our sewage.
Most of us don’t think much about what happens after we flush the toilet. Most of us probably assume that the substances we flush go “somewhere” and are dealt with safely. But we typically don’t think about it beyond that.
Most of us also probably don’t think about what’s in the ocean or lakes we swim in. Since others are swimming, jumping in is just fine. But our waterways are far from clean. In fact, at times they are incredibly filthy. In the US, we are dumping 1.2 trillion of gallons of untreated sewage into the environment every year. Just New York City alone discharges 27 billion gallons into the Hudson River basin annually.
How does this happen? Part of it is the unfortunate side effect of our sewage system design that dates back to over a century ago when cities were smaller and fewer people were living so close together.
Back then, engineers designed the so-called “combine sewer overflow systems,” or CSOs, in which the storm water pipes are connected to the sanitary sewer pipes. In normal conditions, the sewage effluent from homes flows to the treatment plants where it gets cleaned and released into the waterways. But when it rains, the pipe system becomes so overwhelmed with water that the treatment plant can’t process it fast enough. So the treatment plant has to release the excess water through its discharge pipes—directly, without treatment, into streams, rivers and the ocean.
The 1.2 trillion gallons of CSO releases isn’t even the full picture. There are also discharges from poorly maintained septic systems, cesspools and busted pipes of the aging wastewater infrastructure. The state of Hawaii alone has 88,000 cesspools that need replacing and are currently leaking 53 million gallons of raw sewage daily into their coastal waters. You may think twice about swimming on your Hawaii vacations.
Overall, the US is facing a $271 billion backlog in wastewater infrastructure projects to update these aging systems. Across the Western world, countries are facing similar challenges with their aging sewage systems, especially the UK and European Union.
That’s not to say that other parts of the planet are in better shape. Out of the 7+ billion people populating our earth, 4.2 billion don’t have access to safe sanitation. Included in this insane number are roughly 2 billion people who have no toilet at all. Whether washed by rains or dumped directly into the waterways, a lot of this sludge pollutes the environment, the drinking water, and ultimately the ocean.
Pipes pour water onto a rocky shore in Jakarta, Indonesia.
Tom Fisk
What complicates this from an ocean health perspective is that it’s not just poop and pee that gets dumped into nearby waterways. It is all the things we put in and on our bodies and flush down our drains. That vicious mix of chemicals includes caffeine, antibiotics, antidepressants, painkillers, hormones, microplastics, cocaine, cooking oils, paint thinners, and PFAS—the forever chemicals present in everything from breathable clothing to fire retardant fabrics of our living room couches. Recent reports have found all of the above substances in fish—and then some.
Why do we allow so much untreated sewage spill into the sea? Frankly speaking, for decades scientists and engineers thought that the ocean could handle it. The mantra back then was “dilution is the solution to pollution,” which might’ve worked when there were much fewer people living on earth—but not now. Today science is telling us that this old approach doesn’t hold. That marine habitats are much more sensitive than we had expected and can’t handle the amount of wastewater we are discharging into them.
The excess nitrogen and phosphorus that the sewage (and agricultural runoff) dumps into the water causes harmful algal blooms, more commonly known as red or brown tides. The water column is overtaken by tiny algae that sucks up all the oxygen from the water, creating dead zones like the big fish kills in the Gulf of Mexico. These algae also cause public health issues by releasing gases toxic to people and animals, including dementia, neurological damage, and respiratory illness. Marshes and mangroves end up with weakened root systems and start dying off. In a wastewater modeling study I published last year, we found that 31 percent of salt marshes globally were heavily polluted with human sewage. Coral reefs get riddled with disease and overgrown by seaweed.
We could convert sewage into high-value goods. It can be used to generate electricity, fertilizer, and drinking water. The technologies not only exist but are getting better and more efficient all the time.
Moreover, by way of our sewage, we managed to transmit a human pathogen—Serratia marcescens, which causes urinary, respiratory and other infections in people—to corals! Recent reports from the Florida Keys are showing white pox disease popping up in elk horn corals caused by S.marcescens, which somehow managed to jump species. Many recent studies have documented just how common this type of pollution is across the globe.
Yet, there is some good news in that abysmal sewage flow. Just like with plastic pollution, realizing that there’s a problem is the first step, so awareness is key. That’s exactly why I co-founded Ocean Sewage Alliance last year—a nonprofit that aims to “re-potty train the world” by breaking taboos in talking about the poop and pee problem, as well as uniting experts from various key sectors to work together to end sewage pollution in coastal areas.
To end this pollution, we have to change the ways we handle our sewage. Even more exciting is that by solving the sewage problem we can create all sorts of economic benefits. In 2015, human poop was valued at $9.5 billion a year globally, which today would be $11.5 billion per year.
What would one do with that sh$t?
We could convert it into high-value goods. Sewage can be used to generate electricity, fertilizer, and drinking water. The technologies not only exist but are getting better and more efficient all the time. Some exciting examples include biodigesters and urine diversion (or peecycling) systems that can produce fertilizer and biogas, essentially natural gas. The United Nations estimates that the biogas produced from poop could provide electricity for 138 million homes. And the recovered and cleaned water can be used for irrigation, laundry and flushing toilets. It can even be refined to the point that it is safe for drinking water – just ask the folks in Orange County, CA who have been doing so for the last few decades.
How do we deal with all the human-made pollutants in our sewage? There is technology for that too. Called pyrolysis, it heats up sludge to high temperatures in the absence of oxygen, which causes most of the substances to degrade and fall apart.
There are solutions to the problems—as long as we acknowledge that the problems exist. The fact that you are reading this means that you are part of the solution already. The next time you flush your toilet, think about where this output may flow. Does your septic system work properly? Does your local treatment plant discharge raw sewage on rainy days? Can that plant implement newer technologies that can upcycle waste? These questions are part of re-potty training the world, one household at a time. And together, these households are the force that can turn back the toxic sewage tide. And keep our oceans blue.