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How machine learning can save your life

Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

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Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

But what if we could have predicted the outbreak months before it happened, buying us time to take proactive measures to contain it and curb its spread?

With access to overwhelming volumes of data, the computational power needed to store and analyse this data in real time, and sophisticated algorithms that can find patterns in the data and alert authorities to health problems before they become, well, problems, pandemics don’t have to be as devastating as they have been in the past.

In fact, with advanced data analytics, we can better manage any disease – long-term, short-term or pandemic – resulting in better patient treatment, more efficient use of resources and cost savings.

It’s been done before.

By analysing data from social media, blogs, online forums and keyword searches, we were able to predict the 2012-2013 US flu season three months before the Center for Disease Control (CDC) issued its first official warning.

Imagine the impact if the same analytical power was applied across the entire healthcare spectrum – not only on a national and global level, but right down to the individual level.

Data evolution

In the past, health workers relied on manually intensive, paper-based systems to record infections and deaths during disease outbreaks. Not only was it easy for errors to slip through but because the data was anecdotal and historical, authorities did not get a complete understanding of the reach and impact of the outbreak.

During the Ebola outbreak, the CDC adopted a mobile data collection system that enabled health workers to instantly submit information to a database via text messages. This low-cost method of information gathering not only resulted in fewer errors but also allowed analysts to draw up detailed maps of population movements, which made it easier to understand how the disease was likely to spread, and where to set up treatment centres.

While this was certainly an improvement on the paper-based systems of old, the drawback was that mobile data was historic and did not provide researchers with the ability to track developments and population movements in real time.

Data-driven action

But mobile phones are just one source of data. Today, health authorities can overlay thousands of data sources – including social media, health and physician reports, keyword searches, media reports, transactional data from retailers and pharmacies, airline ticket sales, geospatial data and more – to not only better manage diseases and outbreaks when they do happen, but to see them coming months in advance – and what could happen if we don’t act on the information.

By mining structured and unstructured data, we can track the movements of infected populations and who they come into contact with; we can measure the success of containment policies, education campaigns and treatments – and what to do if they’re not working; we can determine the effect of weather and other environmental factors on the spread of diseases.

Never before have we been able to act on information to save lives, not just during pandemics but through better understanding and treatment of diseases.

Personalised treatment

Until now, standard treatments for diseases such as cancer and HIV have been applied to all patients, regardless of their unique profiles and with little understanding as to why some people respond well to certain treatments and others don’t.

But by analysing and creating ‘medical maps’ of individuals that take into account their anatomy, physiology, DNA, RNA and chemical composition, doctors can prescribe personalised treatments that have a greater chance of success.

There are many other benefits of data analysis in healthcare:

·        Personalised treatment can result in fewer hospital admissions and can produce faster results and better experiences for patients;

·        By better understanding the impact of lifestyle and diet on health, medical aid providers can educate their members with the aim of improving their health, which could result in cost savings for both the provider and the member;

·        Governments can use data to develop proactive approaches to protecting and promoting public health, to prioritise services and to find ways to cut costs so that they can provide healthcare to more citizens.

·        By sharing data and results from clinical trials and combining that data with academic, patient and industry data, medical researchers can better understand the genetics of viruses, why some strains are more deadly than others, and why some people are more resistant to viruses. This could spark innovation and generate new insights that ultimately improve treatment and outcomes.

AI and machine learning

As the use of intelligent algorithms, machine learning and natural language processing becomes more entrenched in advanced data analytics, technology will increasingly supplement the skills of humans to produce faster and more accurate medical diagnoses.

We’re already seeing successful applications of artificial intelligence (AI) in predicting relapse in leukaemia patients and in distinguishing between different types of cancer.

Machine learning can extract valuable insights from unstructured data like clinical notes and academic journals to provide even larger datasets that will transform the medical industry into a proactive front against diseases.

There are plenty of doomsday theories about how machines will supersede our intelligence and rise against us. But there aren’t enough stories about the potential of data analytics, AI and machine learning to supplement human skills and knowledge to drastically changes lives for the better – and even save them. Right now, it’s looking more likely that machines will actually help us to live longer – and I don’t know many people who would object to that.

 

  • ANESHAN RAMALOO, ‎Data Scientist and Senior Business Solutions Manager at SAS.

Africa News

Wikipedia wants more Africa

At the recent Wikimania conference in Cape Town, a key focus was on increasing more regional contribution to the world’s largest free, collaboratively-built online encyclopaedia.

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The 14th annual Wikimania 2018 conference, the annual gathering of volunteers from around the world to celebrate Wikipedia and the Wikimedia projects, is expected to bring together over 500 volunteers from around the world to discuss and share ideas around the future of Wikipedia and free knowledge globally.

Wikimedia sites are read approximately 15 billion times a month globally, however only a small portion of volunteer Wikipedia editors come from Asia, Africa, and Latin America combined.

Anyone can edit Wikipedia in any of its almost 300 different language versions including Swahili, Hausa, Amharic, Arabic and Afrikaans versions.

“To achieve knowledge equity we need to have more voices represented in our community.  This is why we are creating an inclusive environment for people from all over the world to contribute knowledge in a way that considers custom, language, access to bandwidth, and more,” said Ellie Young, Conference Organizer for Wikimania.

Ghanaian Wikipedia contributor and free knowledge activist Felix Nartey says that some of the primary barriers to contribution from people living in Africa is lack of time and lack of access to an enabling environment (computers and access/affordability of internet).

“We have been engaging with our communities and holding a number of successful editathon sessions. What is apparent is that African people have a real appetite to see themselves represented on this platform. They want to see their content and their languages on Wikipedia and are crashing through some of the structural barriers to do so,” said Mr. Nartey.

For example, through a collaboration with the Social Theory Course at Ashesi University in Ghana, students have been given class assignments which have led to contributions of their research and term papers on Wikipedia through the Wikipedia Education Program model.

Across other parts of Africa, organised thematic workshops targeted at bridging the gender gap and other systematic biases that exist on Wikipedia have also been held.

Work to create more regional content also continues. In South Africa, Afrikaans and isiZulu are the most active language Wikipedias other than English.

“If you are passionate about a specific topic or piece of local history, or if you would like to see more articles in your own language, register and start making your contributions. The only way we are going to shift the content bias is by adding content that represents a more diverse user base,” said Douglas Scott, President of the Wikimedia Chapter of South Africa.

With over 5 million articles already on English language Wikipedia, Mr. Scott says that more African contributors can get involved by creating an account on Wikipedia and testing out different ways to edit — whether it’s fixing a grammatical error or adding a citation to an existing article, creating a new article, or asking other volunteer editors for support in reviewing a draft article you created.

Articles on Wikipedia need to have verifiable references and sources. This means that facts must be drawn from recognisable publications and institutions. A great way for more African contributors to get involved is to join a WikiProject around specific areas of interest. WikiProjects consist of groups of contributors who work together to create and improve articles about a specific topic on Wikipedia.

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Africa News

Africa’s fintech is migrating

Africa’s fragmented markets and lack of legacy foreign exchange trading infrastructure means that the continent has become a melting pot of fintech activity and innovation, writes TIM HUTCHINSON, Head of Digital for Financial Markets, Standard Bank.

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The evolution to electronic foreign currency trading in Africa, while slow to start, is today gaining tremendous traction. 

In South Africa, only five years ago, almost 90% of foreign currency trades happened over the telephone. Today, despite challenges around illiquidity and complicated political and capital control environments, approximately 75% of trades are conducted digitally, with a mere 25% conducted on the phone. 

With 57.6% of the world’s 174-million active registered mobile money accounts in Sub-Saharan Africa, the continent is becoming a world leader in fintech generally, and in mobile money in particular. As African citizens and business people transact globally, Africa’s highly developed fintech culture is not only deepening on the continent, but is also migrating out of Africa.  

The foreign exchange flows that Africa’s expanding fintech culture supports are very important to the continent’s financial services providers, most of whom are developing fintech capabilities or partnering with the most popular or effective home-grown African fintech’s to ensure that they capture this flow.

Standard Bank has been an integral part of driving this rapid evolution to digital in Africa’s foreign exchange trading landscape.  

In order to function as an effective market maker, we need to source liquidity in market. We also need to, instantly, formulate risk-based pricing in an ever-changing world. Thereafter we need to distribute price. 

In Africa this requires developing solutions that allows retail, corporate and institutional customers to access foreign exchange markets across multiple jurisdictions. At the same time in most markets, “we also need to show central banks what we are doing,” adds Mr Hutchinson. All transactions need to be transparent and electronically traceable so that local authorities are prepared to approve digital trades. 

Today, however, banks are not only expected to provide the systems and networks to facilitate basic transactions but are also required to provide insight and guidance beyond pure execution by offering additional value-based services across research, hedging and, most importantly, settlement capability. Currency research for example, is increasingly a big client requirement. Having on the ground experience and local expertise as well as the ability to deliver this digitally, “differentiates Standard Bank’s distribution capabilities in this regard”. 

In addition, banks are also increasingly required to inform and guide clients through the broader economic, legal and political landscapes in which transactions occur. For example, one of the considerations in developing Standard Bank’s digital capability was how to combine market intelligence and research with real-time pricing, trade execution and post-trade services. Today it is not enough just to execute trades. It is equally important that we advise and inform the broader universe in which trades happen.  

From a technology point of view Regulatory Technology (Regtec), for example, is assisting Africa to manage new regulatory developments in heavily currency-controlled environments. Similarly, the rise in robotic process automation (RPA) and artificial intelligence (AI), “has allowed Standard Bank to develop solutions that leapfrog traditional business problems”. 

Digital trading in Africa is also evolving in its own often very different way. We have found that it is not just a question of importing developed world systems. Our approach with clients is to work with them to help understand their internal needs in terms of governance and operational efficiency. We then partner with clients to develop and implement digital solutions that talk to the heart of their business need. 

Standard Bank’s own Business Online (BOL) platform provides an example of how the bank has built digital transaction capabilities that exactly meet client need. BOL, for example, allows clients to view balances across the continent while making third party currency payments and also supporting general cash management. This kind of broad, business-wide digital cash view and capability puts control back in the hands of the clients while also allowing clients, rather than the bank, to manage their own cash flow.

From an Institutional perspective it’s very important to be able to offer customisable solutions to clients managing money on behalf of their investors. Standard Bank’s investment in Application Programming Interface (API) technology, for example, is tracking exactly its client’s growing ability to build these capabilities into their own systems. 

On the retail side Standard Bank’s SHYFT app – a digital wallet allowing global transactions in USD, EUROS, GBP and Australian dollars has extended this control element to the man in the street. SHYFT has been recognised both globally and locally for its innovation.

Standard Bank presents a very compelling, unique and globally competitive digital trading proposition to local and developed world clients seeking to access Africa. Our footprint across 20 territories – most at different levels of digital development – provides a compelling pan-African proposition for global and local clients alike.

While Africa’s record in digital adaptation and innovation is impressive, the technology part is often the easier part to implement. The human and cultural systems, and client behaviour changes, required to give this digital evolution life – like getting customer analogue systems to start pricing electronically to make trades visible 24/7 – is often a lot harder to achieve than the technology upgrade. In short, bank employees, customers and regulators all need to undergo fundamental cultural shifts in how they do things and understand the world.

It is often these broader cultural and market shifts that Standard Bank as a pan-African bank is called on to advise as clients seek to understand and engage Africa effectively. 

Given the rapid pace of digital evolution within Africa’s varied market, customer, legislative and cultural landscapes, we need to balance customer value and efficiency – and regulatory pressures to be more transparent – with what is, in the long run, best for the market. 

As a pan-African bank inextricably committed to the growth and success of the continent, Standard Bank’s digital journey requires a judicious blend of developed world technology with African insight and innovation. This blend should be capable of balancing customer need and legislative oversight in the development of efficient and inclusive markets that sustain long term growth. 

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