AI and the future of healthcare

AI and the future of healthcare

Artificial Intelligence on the Horizon

The Future of Healthcare

(Second in a Series)

Discussed much more thoroughly in the last article AI in Banking, Artificial Intelligence (AI) is a powerful force for business. Does it have a place in Healthcare, too? You better believe it.

In this country, healthcare is a business, even if it is full of altruistic individuals that are just seeking to help others. We thwart disease; we repair damage; we cope with aberrations in bell-curve physiology; and most importantly, we make lives better.


But that doesnt work very well without a solid business foundation! We still need to know where the money is coming from, where it is going, how it is invested, and what constitutes a good purchase decision for everything from a scanning electron microscope, right down to the price of cotton swabs.

For example, an additional MRI scanner would undoubtedly increase the daily throughput for our clients, but would it be better to hire a couple more technicians to keep the current machines running 24 hours per day? If a patient has a choice of waiting three weeks for an MRI or coming in today at 3 AM, which will they choose? People with day-to-day jobs might not have the time or be able to afford time-off during “office hours” for an appointment.

Easing the Workload

AI is the perfect tool for analyzing data, and although that problem may seem simple, there are dozens more that could be handled by Artificial Intelligence. An AI could do all the paperwork for a family physician. Insurance claims are mind-numbing in this country and take about half of a doctors time. If s/he sees patients for six hours, there is going to be six hours of paperwork to accompany that.

Remote Medicine

The Royal Flying Doctor Service (RFDS) was formed in Australia in 1928, by Rev. John Flynn by combining two fledgling technologies: the ability to fly with airplanes, and the ability to communicate with radios. Rev. Flynn had established the Australian Inland Mission (AIM) in 1912 to provide remote communities with medical aid.

The Outback of Australia is so vast that the AIM wasnt up to the task. Too many people were too far away even from the hospitals dotted throughout the continent. Putting doctors in planes and equipping them with radios meant that medical assistance was usually only a couple of hours away. The RFDS flew 20,000 miles in their first year, over the course of 50 flights.

AI to the Rescue

The advent of Telehealth has made it possible to deliver healthcare to small, remote communities. This is already common in isolated communities in Canada and Australia. Doctors, Nurse Practitioners, Nurses, mental health professionals, and many others can deliver their services by video link.

In a clinical environment, the remote medic can read real-time ECGs, listen to heartbeats and lung function, and have the patient or an aide perform physical manipulations, as well as just listening to the patient. Its not perfect, but so much better than waiting months for treatments when going to a bigger city, or waiting for when a medical professional visits.

AI, on the other hand, could fill a role with an adaptation of our modern robot surgeons that are already in use. A remote doctor could manage the robot (complete with their friendly smiling human face visible to the patient), with its highly sensitive and well-developed feedback system, to perform tasks as if s/he were actually in the room. The patient, knowing that a human was at the other end of the machine, could become accustomed to this activity.

The AI would eventually become so knowledgeable that for everyday consulting it could manage entirely on its own. At the opposite end of the spectrum, robotic surgeons would continue to gather empirical knowledge from all the best surgeons in the world. While still monitored by a human surgeon for safety, this would one day allow flawless surgery of any kind. Everything in between these two extremes would be the domain of medical professionals, freeing up more time to interact with people.

AI Enters the Patient Care Arena

In some places, notably Japan where they love their robots, big white (easy to sanitize) friendly robots now pick up patients to place them on gurneys or in bathtubs eliminating injuries for orderlies and nurses. The unit must be smart enough to calculate load and balance, but also capable of detecting pressure, and supporting (often elderly) patients without injury. Of course, theyre still guided by humans

The friendly Panda robot in the pictures deliberately doesnt look human because that might frighten Alzheimers patients. But it can lift someone from the floor and place them in bed, help them to stand, help them to walk, seat them in a wheelchair, and other strenuous activities that result in hospital worker injuries. More importantly, like here, the population in Japan is aging and will need support that might be beyond the capability of the human staff, so they are aggressively looking for solutions from Artificial Intelligence.

Organization Skills

Surgical schedules that make the best use of available space and equipment would streamline operations, allowing more to get done, in less time, at a lower cost. The same can be done in Radiology, Physiotherapy, and even the Laundry Department. There is no such thing (yet) as a perfectly organized hospital—theres room to improve, and AI will get us closer.

Data Protection

The onslaught of cyber assaults has not diminished. Clinics and hospitals are among the most vulnerable because they have so many out-of-date computer programs still in use that are no longer supported by the manufacturer. Updating web browsers is free in most cases. Some hospitals have refused to say “Our employees arent allowed to use the computers on the internet, so we dont need that,” and we all know how employees always obey the rules.

Medical professionals leave tablets and laptops lying around all over the hospital, and they are regularly stolen. This puts Personally Identifiable Information (PII) of patients into the hands of criminals.

AI can identify any of these devices, where it is being used, and if the typing, voice, or data entry technique matches the regular user. Even if it locks after 90 seconds, people use such simple passwords that they can be defeated in just a few minutes. AI can stop the misuse.

An AI, capable of thinking much faster than a human being, could recognize a cyber attack in milliseconds and isolate the affected system. This leaves the remainder of the Computer System up and running, without even a noticeable blip to all of the other users.

Better Analysis than Humans

MRIs, X-rays, PET, CT, and CAT scans are more efficiently and accurately interpreted by computers and AI than humans. The machine can spot tiny variances that a human might overlook, as well as patterns that are located too far apart on an image for a human to make an association.

AI Diagnosticians

Having an app on your phone which possesses an encyclopedic medical knowledge database will make it possible to have a consultation on the spot. The difference is that this “ChatBot” is a Medical Expert System,  armed with your medical history, and genuine knowledge, not some convincing-but-misinformed “expert” on the internet.

AI Nursing

Stay-at-home patients can consult as often as they like with Molly, the Nurse from  Sensely. It, or she, is designed for chronic conditions, to track health, and offer support, even for palliative care. Voice recognition and deep empathy are key factors, but it also connects seamlessly with electronic monitoring equipment, so it knows what is going on at precisely the moment it is connecting with the patient.

AI Drug Development

One Pharmaceutical company had an AI comb through its database looking for existing molecules that would be effective in combating an Ebola outbreak. What could have taken months or years was accomplished in a day, producing two new drugs that could go to testing & trials. Drugs could be cheaper, tested sooner, and save millions of lives with the help of AI.

AI Problem Tracking

This is what AI is best suited for: analyzing data. IBM’s Watson computer, which you may recall beat the all-time Jeopardy champion, now lives on the internet where people can people utilize its data analysis skills for any purpose. Zorgprisma Publiek,  in the Netherlands, uses public health records (which include clinic names, the condition treated, drugs prescribed, and treatment strategies) to inform clinics about misdiagnoses and improper treatment schedules so they can identify their common errors and improve their methodology.

AI Training of Medical Personnel

Familiarizing medical professionals with the capabilities of artificial intelligence can be performed by AI systems. These hands-on people wouldn’t need to be intimidated by introducing a layer of technology. Equipped with a high-level voice recognition interface, interactions would be like talking to a friend, and this could get these already intelligent people up to speed in short order.

Once that was accomplished, doctors could “consult” with the AI Expert System, to analyze problems, compare treatment strategies, and project outcomes. This introduces a whole new aspect of personalized medicine, making it even more customized to each person.

The Takeaway

With the invention of modern medical telemetry devices, the amount of information being generated is incredible. Where no human could sort through all the incoming data, AI is ideally suited to the task. The more connected we are, the more personalized the data assessment can be.

The amount of exercise in a given period, combined with actual blood pressure, heart rate, oxygenation, and more could allow an AI to customize medical advice. It could alert at-risk individuals about problems in the early stages when they are still easy to treat and have the best chance of a successful outcome.

Not only will this provide an improved health status for the average person, but it will manifest itself as fewer expensive claims against insurance plans. As we all know, the healthier you are, the less expensive you are. AI is the future of medicine!

Originally posted on WildFire Force blog.


AI and the future of healthcare

How will AI change the future of banking and financial services?

How will AI change the future of banking and financial services?

Artificial Intelligence on the Horizon

The Future of Banking

(First in a Series)

Introduction

Humanity has been on the road for a very long time—from the beginning, when each individual had to collect sufficient food to survive every single day—to the point where we invented agriculture. At that point, we moved from 99% survival and 1% reproduction to a brand new model.

Growing food marked the introduction of leisure. Since then, every step in our evolution has proceeded along the lines of doing more and more with less and less. You might recall the 1899 story of Charles H. Duell, Commissioner of the U.S. Patent Office, lobbying President McKinley for its closure, claiming that “everything had already been invented.” Nonsense, of course (or at least highly apocryphal), but demonstrative of how some people can appear to be short-sighted.

Perspective

On a timescale where the entire universe was contained within a single calendar year, it would only be in the first hours of December 31st of that year where apes and monkeys had their evolutionary split. At 8:00 PM of that day humans and chimpanzees experienced their evolutionary split. Around 9:30 that night, humans began to walk upright for the first time.

If it was the very last second of that imagined December 31st right now, it was only an hour and a half ago, at 10:30 PM, that our brains began to grow from 1 pound all the way up to 3 pounds—and that was the Dawn of Intelligence. It was only 8 minutes ago that the first Modern Humans evolved. And it was only between 1 and 4 minutes ago that we migrated to all the continents of the world (except Antarctica).

The Last Minute

The bulk of human evolution occurred in just the last 8 minutes, but what we identify as our history all happened in the last minute. With only 50 seconds to go before midnight our cave-dwelling ancestors were sketching prehistoric animals on the wall, the most recent Ice Age was coming to an end, and sea level was 400 feet lower than it is today.

About 30 seconds ago, the Mediterranean culture arose giving us agriculture, which led to the first permanent settlements. Just 15 seconds ago marked the beginning of Dynastic China. About 6 seconds ago was the time of the Old Testament and Buddha, with Christ and Mohammed born in the last 3 or 4 seconds. One second ago, Columbus set foot in North America.

The 100-year lifespan of a human on this scale is less than one-quarter of a second. It is only within the last 0.125 seconds that we gained computers, the Internet, microcomputers, cell phones, and the Totality of Human Knowledge doubling every 18 months.

Smarter, or Overloaded?

Weliterally have gained twice the knowledge that the Human Race accumulated since we first evolved, in just the last 18 months. In another year and a half, it will have doubled again. And the process is speeding up. Consider this YouTube video made by IBM, showing the world’s smallest movie. It’s a brief (93 seconds) animation called A Boy, and his Atom made entirely with single atoms, manipulated at the atomic level, and magnified 100 million times so we can see it.

We’re learning to do so much, and so fast, that the information is accumulating faster than we can use it. This is a problem. Artificial Intelligence is the answer to the problems encountered in data science use cases in finance, and many other fields besides.

Machine intelligence is the last invention that humanity will ever need to make—Nick Bostrom, TED speaker, Vancouver, B.C.

Electronic Overlords?

Movies like Terminator tend to paint pictures about the downfall of humanity because an AI thinks humans are a threat. The movie’s Skynet is probably not something we need to worry about, however.

We should make sure we teach the AI what humans would approve of, and what would be a bad idea. A nebulous goal of “eliminate human unhappiness” might end up with it wiping out the race—no people, no unhappiness, right? We had better have a good, well-described goal for it to work on before we flip the switch. Keep the stories of The Monkey’s Paw and King Midas in mind, and we should be fine. Just don’t expect it much before 2040 or 2050.

State of the Art

Our current AI systems are now quite efficient at interpreting natural language. You can speak to your phone assistant with high accuracy and get the results you want such as weather reports, paying your bills, scheduling of appointments, or finding information online. This is precisely what we need in machine learning use cases in banking.

AI is now achieving >80% accuracy interpreting human facial expressions, the emotional content of sentences; it performs actions millions of times to work out strategies that are successful. It also categorizes those who fail to get the desired results. This amounts to learning, and although it may be primitive, it is still surprisingly good.

Banking Will Benefit

Meeting Customer Expectations

People assume things will happen seamlessly, as they have come to experience it on Google and Facebook. Those companies have been employing AI systems and collecting information about us for so many years that it is getting easier to predict what sort of news article, advertisement, or video that we want to see next. Customers want their banking to be the same way, offering precisely what they want, at the time they most likely need it. If you are not using AI, you’ll be seen as archaic, and clients will migrate to banks that fulfill their needs before they need to ask.

Predictive Selling to Customers

Uses of this information for banks mean that they can offer services as appropriate. If a customer buys or leases a new car every five years, it would make good sense to send them a rate-guarantee at 55 or 56 months into their contract, to encourage them to arrange their financing with that particular bank.

If their debt seems to be climbing to an unmanageable level, something a human being might not notice, sending an offer of a consolidation loan at a lower percentage, or arranging a low rate line of credit based on the equity of their home might allow them to keep on top of their finances. Such AI use cases in finance could help assure that the banking institution increases the likelihood of keeping a good customer, and reduces the chance of significant loss due to bankruptcy.

Chat Bots

One of the ways to achieve that is through Chat Bot Expert Systems. Collecting all the empirical knowledge of the 100 best heart surgeons in the world and programming it into a robotic surgeon would allow flawless heart surgery (one day, in the far future). Having all that combined knowledge with light-speed calculations and analysis would mean there would always be an answer to a complication. If a human had dealt with the problem before, the AI could solve the problem; if not, it could combine the accumulated knowledge and work out a new solution based on all that experience.

With customers, AI use cases in banking, such as an expert financial system, could take all the information about the client (age, past investment strategies, goals, preferences), and create financial advice. Chat Bots have become so sophisticated that sometimes it becomes impossible to differentiate them from human beings. Those workers formerly answering fairly conventional questions over and over again could then be redeployed to handle more complex issues.

Trend Identification

AIs can spot relationships in bulk information that would elude a human being. Companies right now are faced with a massive wave of retiring Baby Boomers. Very few saw this coming despite very clear signs. Now they are scrambling to acquire replacements for their best people.

If AI Technology had been sophisticated enough to be employed by HR, we could have had years of warning. That would have allowed for hiring college graduates and exposing them to the existing experts before they retired, allowing them to mentor these neophytes. All that knowledge would not be lost.

Anti-Money Laundering

Crooks are getting smarter about fooling the casual observer with their financial actions. It might take a forensic accountant to identify instances of illegal money laundering.

This is not so when you combine machine learning use cases in finance with artificial intelligence. AI, armed with the knowledge of hundreds of forensic accountants, could quickly spot telltale activity. It makes the Federal Reserve, the FBI, and in some cases, the CIA happy; it increases the bank’s reputation; it increases the likelihood of appropriate taxation for the IRS; and, more than likely, it puts a significant dent in crime.

Identity Analytics

An AI will be able to recognize a customer more reliably than relying on mere encryption and a password. It will know the tempo that a person types, where they hesitate or dwell, their physical appearance on video, and will be able to distinguish between a photo and a blinking, breathing person, with characteristic eye-movements.

It also works for identifying employees for access to restricted areas, or the ability to perform specific actions. It can even identify a pre-actions characteristic of a robbery before it happens, and alert staff, security, and the police before it occurs.

Robotic Process Automation

AI can recognize problems much sooner than at Quarterly Report time, allowing corrective actions to be taken immediately, potentially saving millions of dollars per year. This makes it increasingly accurate and eliminates the extraordinary workload of period-end efforts. The financial status, reliability of investments, and all the associated information would constantly be on-hand, and accurate up to that very moment when the inquiry is made.

Insightful Trading

Asset allocation and forecasting for the bank itself or its customers could allow for much wiser investment decisions. AIs could easily outperform Day Traders once they had been programmed with expert knowledge about market trends, meaning they could make trades to take advantage of the tiniest fluctuations, getting in and out of stock faster than a human could even decide to buy in the first place.

Fraud Recognition

AIs can recognize data patterns and deviations from the norm in real time. If three pensioner’s accounts suddenly transfer their balances to a new account owned by none of them, the AI could freeze that account until a human can investigate. That is only a gross example; AIs could be sensitive to much more subtle clues than that.

Since banks are responsible for these losses once a customer has informed them, it will certainly pay dividends to implement something like this early. Aside from the financial loss, there could also be significant penalties from regulatory agencies if the fraud was determined to be possible because of a lack of proper oversight.

Predicting the Future

Understanding customers’ tendencies, and how they use the resources of the bank, would be labor intensive for an employee, but child’s play for an Artificial Intelligence. Clients seldom know about all of the offerings of a particular financial institution, whereas an AI will know every single aspect of those services and the tendencies of the individual customer.

It can customize a package for that client that suits their needs perfectly. That creates a happy client that isn’t going to move to another financial institution. You have now achieved customer retention and built loyalty which will be reflected in recommendations to new customers.

The Takeaway

Artificial Intelligence is going to have an impact on data science use cases in banking. The same can be said for Finance, Health Care, or Big Pharma. AI will have a significant influence.

Most businesses have recognized the significance of Big Data. The need for Data Scientists has grown exponentially to the point that they’re getting rather hard to come by in this economy. AI is going to help with that.

Once we have some algorithms to teach an AI to analyze the data we can free up a lot of humans to do more critical work. In its current state, this is what AI is best at—the drudge work of data analysis. Whether it’s answering common questions for customers as a ChatBot, or finding fundamental flaws in investment strategies, AI is the grease for our economic engine. It will make everything run better, faster, and at a reduced cost.

 


How will AI change the future of banking and financial services?