3 Ways Machine Learning Is Benefiting Your Healthcare

Judith Kniepeiss our consultant managing the role
Posting date: 2/13/2020 9:19 AM
With Data-led roles leading the list in the World Economic Forum’s ‘Jobs of the Future’ report, it is no surprise that Data Science continues to be the main driving force behind a number of technological advancements. From the Natural Language Processing (NLP) that powers your Google Assistant, to Computer Vision identifying scanning pictures for specific objects and the Deep Learning techniques exploring the capability of computers to become “human”, innovation is everywhere. 

It’s unsurprising, then, that the world of healthcare is fascinated by the possibilities Data Science can offer,  possibilities which could not only make your and my life better, but also save several thousands of lives around the world.

To just scrape the surface, here are three examples of how Machine Learning (ML) techniques are being used to benefit our healthcare. 

COMPUTER VISION FOR IMAGING DIAGNOSTICS 


Have you ever had a broken leg or arm and saw a x-ray scan of your fracture? Can you remember how the doctor described the kind of fracture to you and explained where exactly you can see it in the picture?

The same thing that your doctor did a few years ago, can now be done by an algorithm that will identify the type of fracture, and provide insights into how you should treat it.

And it’s not just fractures; Google's AI DeepMind can spot breast cancer as well as your radiologist. By feeding a Machine Learning model the mammograms of 76,000 British women, Google’s engineers taught the system to spot breast cancer in a screen scan. The result? A system as accurate as any radiologist. 

We‘ve already reached the point where Machine Learning and AI can no longer just outsmart us at a board game, but can benefit our everyday lives, including in as sensitive use-cases as the healthcare industry.

NLP AS YOUR PERSONAL HEALTH ASSISTANT 


When we go to our GP, we go to see someone with a medical education and clinical understanding who can evaluate our health problems. We go there because we trust in the education of this person and their ability to give us the best information possible.

However, thanks to the rise of the internet, we’ve turned to search engines and WebMD to self-diagnose online, often reading blogs and forums that will convince us we have cancer instead of a common cold. 

Fortunately, technology has advanced to the point where it can assist with an on-the-spot (much more accurate) evaluation of your medical condition. By conversing with an AI, like the one from Babylon Health, we can gain insights into possible health problem, define the next steps we need to take and know whether or not we need to see a doctor in person. 

There’s no need to wait for opening times or to sit bored in a waiting room. Easy access from your phone democratises the process and advice can be received by anyone, at any time.   

DEEP LEARNING DRAWS CONCLUSIONS BETWEEN MEDICAL STUDIES


Despite their extensive qualifications, even medical researchers can feel overwhelmed by the sheer amount of Insights and Data that are gathered around the world in hospitals, labs, and across various studies. No wonder it’s not uncommon for important Insights and Data to get forgotten in the mix.

Once again, Machine Learning can help us out. Instead of getting lost in a sea of medical data, ML algorithms can dig deep and find the information medical researchers really need. By efficiently sifting a through vast amounts of medical data, combining certain datasets and providing insights, ML sources ways for treatments to be improved, medicines to be altered, and, as a result, can save lives.

And this is only the beginning. As Machine Learning continues to improve we can expect huge advances in the following years, from robotic surgery to automated hospitals and beyond.

If you’re an expert in Machine Learning, we may have a job for you. Take a look at our latest opportunities of get in touch with one of our expert consultants to find out more. 

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The Search For Toilet Paper: A Q&A With The Data Society

We recently spoke Nisha Iyer, Head of Data Science, and Nupur Neti, a Data Scientist from Data Society.  Founded in 2014, Data Society consult and offer tailored Data Science training for businesses and organisations across the US. With an adaptable back-end model, they create training programs that are not only tailored when it comes to content, but also incorporate a company’s own Data to create real-life situations to work with.  However, recently they’ve been looking into another area: toilet paper.  Following mass, ill-informed, stock-piling as countries began to go into lockdown, toilet paper became one of a number of items that were suddenly unavailable. And, with a global pandemic declared, Data Society were one of a number of Data Science organisations who were looking to help anyway they could.  “When this Pandemic hit, we began thinking how could we help?” says Iyer. “There’s a lot of ways Data Scientists could get involved with this but our first thought was about how people were freaking out about toilet paper. That was the base of how we started, as kind of a joke. But then we realised we already had an app in place that could help.” The app in question began life as a project for the World Central Kitchen (WCK), a non-profit who help support communities after natural disasters occur.  With the need to go out and get nutritionally viable supplies upon arriving at a new location, WCK teams needed to know which local grocery stores had the most stock available.  “We were working with World Central Kitchen as a side project. What we built was an app that supposed to help locate resources during disasters. So we already had the base done.” The app in question allows the user to select their location and the products they are after. It then provides information on where you can get each item, and what their nutritional values are, with the aim of improving turnaround time for volunteers.  One of the original Data Scientists, Nupur Neti, explained how they built the platform: “We used a combination of R and Python to build the back-end processing and R Shiny to build the web application. We also included Google APIs that took your location and could find the closest store to you. Then, once you have the product and the sizes, we had an internal ranking algorithm which could rank the products selected based on optimisation, originally were based on nutritional value.”  The team figured that the same technology could help in the current situation, ranking based on stock levels rather than nutritional value. With an updated app, Iyer notes “People won’t have to go miles and stand in lines where they are not socially distancing. They’ll know to visit a local grocery store that does have what they need in stock, that they’ve probably not even thought of before.” However, creating an updated version presented its own challenges. Whereas the WCK app utilised static Data, this version has to rely on real-time Data. Unfortunately this isn’t as easy to come by, as Iyer knows too well:  “When we were building this for the nutrition app we reached out to groceries stores and got some responses for static Data. Now, we know there is real-time Data on stock levels because they’re scanning products in and out. Where is that inventory though? We don’t know.” After putting an article out asking for help finding live Data, crowdsourcing app OurStreets got in touch. They, like Data Society, were looking to help people find groceries in short supply. But, with a robust front and back-end in place, the app already live, and submissions flying in across the States, they were looking for a Data Science team who could make something of their findings.  “We have the opportunity,” says Iyer “to take the conceptual ideas behind our app and work with OurStreets robust framework to create a tool that could be used nationwide.” Before visiting a store, app users select what they are looking for. This allows them to check off what the store has against their expectations, as well as uploading a picture of what is available. They can also report on whether the store is effectively practising social distancing. Neti explains, that this Data holds lots of possibilities for their Data Science team: “Once we take their Data, our system will clean any submitted text using NLP and utilise image recognition on submitted pictures using Deep Learning. This quality Data, paired with the Social Distancing information, will allow us to gain better insights into how and what people are shopping for. We’ll then be able to look at trends, see what people are shopping for and where. Ultimately, it will also allow us to make recommendations as to where people should then go if they are looking for a product.”  In addition to crowdsourced information, Data Society are still keen to get their hands on any real-time Data that supermarkets have to offer. If you know where they could get their hands on it, you can get in touch with their team.  Outside of their current projects, Iyer remains optimistic for the world when it emerges from the current situation: “Things will return to normal. As dark a time as this is, I think it’s going to exemplify why people need to use Artificial Intelligence and Data Science more. If this type of app is publicised during the Coronavirus, maybe more people will understand the power of what Data and Data Science can do and more companies that are slow adaptors will see this and see how it could be helpful to their industry.”   If you want to make the world a better place using Data, we may have a role for you, including a number of remote opportunities. Or, if you’re looking to expand and build out your team with the best minds in Data, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes. 

Why Businesses Need To Put Fraud Prevention Front And Centre

If Fraudsters are anything, they are opportunists. Once the first new stories about COVID-19 started running, it wasn’t long until they were joined by tales of fraudsters selling face masks and hand sanitiser, asking panicked customers to transfer money and then disappearing without a trace.  And it’s not the first time we’ve seen this. Fraudsters are notoriously wise to periods of heightened sensitivity and uncertainty, often preying on the vulnerable. The 2008 financial crisis saw an increase in email-based phishing scams and a decade’s worth of technological advancements means that Fraud remains a many-headed beast.  Add into the mix a change in working styles and environments, and many businesses are more exposed to potential security breaches than they have been in years. Now, more than ever, companies need to make sure their Data is well protected and secure. THE FIRST LINE OF DEFENCE If you’re part of, or leading, a Fraud Prevention team, there are a number of ways you can support your business and keep on top of the situation. Here are just a few: Increase and update your investigation capacity. This team are the front line of your business’ Fraud defence team, interacting with customers daily and spotting new scams. During an uncertain period, retention and team stability is key. These are the people that understand the day-to-day Fraud challenges you face and will be essential in fighting any future challenges.  Sharing Fraud Prevention knowledge is key. Throughout this crisis, trends will be evolving quickly and working collaboratively across teams, and even other businesses, is the best way to combat this. We consistently hear from Fraud Managers that the key to beating Fraud is to share information and knowledge. Despite this, there is always a hesitation amongst companies to admit that they have been a victim to an attack. Perhaps now is the time to change this. Invest in Machine Learning and real time updates for your Fraud defences. Fraud technology has moved on from script writing in SQL and rule changes. Businesses need a real time reactive response and now is an important time to be embracing new technologies. There are a number AI-driven off the shelf packages available or, for a more bespoke solution, a Fraud Data Scientist can create something internally. Educate your team. It may seem simple, but the Fraud team can play a crucial role in minimising any potential risk from human-error. Educating employees on the risks they may face when working remotely, or what scams they need to look out for, is one of the most effective ways of fighting Fraud.  PREPARING YOUR BUSINESS Success in the fight against Fraud isn’t purely down to the group of individuals that make up the Fraud team. As a business, now is the time to be making decisions that can help you stay ahead of the Fraudsters. Here are some considerations: Consider investing in tech as an your immediate response. Not just to bolster your Fraud defences (although there are plenty of vendors offering AI-based solutions), but also technology for your employees to keep work as normal as possible such a sharing platforms, DevOps technology and video calling networks. One of the best ways to block some of the vulnerability loopholes fraudsters are trying to exploit is to keep working habits as close to normal as possible as you move to a remote solution. Be transparent with your customers. Consumers are being incredibly savvy and noting how businesses respond to the pandemic in a way that could have a big impact when normality returns. But they’re also being more empathetic and are willing to understand difficulties. For example, shopping delivery service Ocado were open and transparent when their system could not initially deal with demand. Having communicated the difficulties, worked through their issues and gone the extra mile to let customers know how they can be supported in this time, the received minimal backlash. There is an understanding that we’re all in this together. Finally, if you have the budget, continue to staff up - particularly in competitive fields such as Data Science. A lot of top Data professionals are currently at home and much more accessible than they have been in a long time. With a number of ways to remotely interview and onboard both permanent and contract staff, if you are able to get begin conversations with them now, you’ll have an edge in what will be a very competitive market come later in the year.  If you’re looking to take your next step in the world of Fraud, we may have a role for you, including a number of remote opportunities.  Or, if you’re looking to expand and build out your Fraud team, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes. 

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