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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

Smart grids needed for Africa’s utilities

Power utilities across Africa should rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem, says COLIN BEANEY, Global Industry Director for Asset-intensive and Energy and Utilities at IFS.

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Africa’s abundant natural resources and urgent need for power mean that it is one of the most exciting and innovative energy markets in a world that is moving rapidly towards clean, renewable energy sources. The continent’s energy industry is taking new approaches to providing unserved and underserved communities with access to power, with an emphasis on smart technologies and greener energy sources.

Power systems are evolving from centralised, top-down systems as interest in off-grid technology grows among African businesses and consumers. And according to PwC, we will see installed power capacity rise from 2012’s 90GW to 380GW in 2040 in sub-Saharan Africa. Power utilities are needing to rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem.

Energy and utilities providers are transforming from centralised supply companies to more distributed, bi-directional service providers. They can only achieve this through the evolution of “smart grids” where sensors and smart meters will be able to provide the consumer with a more granular level of detail of power usage. This shift from an energy supplier to “lifestyle provider” will require a much more dynamic and optimised approach to maintenance and field service.

African companies must thus embrace digital transformation as an imperative. This transformation begins by embracing enterprise asset management to improve asset utilisation. The subsequent steps are enhancing upstream and downstream supply chain management; resource optimisation; introducing enterprise operational intelligence; embracing new technologies such as the Internet of Things, machine learning, and predictive maintenance; and becoming a smart utility.

Embracing mobility to drive ROI

Getting it right is about putting in place an enterprise backbone that accommodates asset and project management, multinational languages and currencies, new energies and markets, visualisation of the entire value chain, and mobility apps. Mobile technologies that support the field workforce have a vital role to play in driving better ROI from utilities’ investments in enterprise asset management and enterprise resource planning solutions.

Today’s leading enterprise asset management solutions feature powerful functionality for mobile management of the complete workflow of work orders – from logging status changes and updates, from receiving and creating new orders to concluding the job and reporting time, material and expenses. Such solutions are easy to deploy and intuitive for end users to learn and use.

Importantly for organisations operating in parts of the continent with poor telecoms infrastructure, connectivity is not an issue. The solutions work offline and synchronises when network connectivity is available. Users can work on any device—laptops, tablets, and smartphones—commercial or ruggedised.

By ensuring that field technicians have easy access to information and processes, the mobile solution enables technicians and maintenance engineers to easily do the following tasks:

·         Create a new work order on the fly and log new opportunities

·         Access both historical and planned work information when requested

·         Permit customers to sign when the job is completed

·         Capture measurements and inspection notes on route work orders

·         Create new fault reports on routing

·         Facilitate documentation through photo capturing

·         Provide easy access to technical data and preventive actions.

The power of mobility allows the engineer to be the origin of all data capture on a service event. They can easily inquire on asset history, record parts used or parts needed for repair, record labour hours, and expenses as they occur, and any notes of repairs performed. When coupled with workforce management tools, such solutions unlock significant productivity gains for utilities who are trying to get the most from their workforce and assets.

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Africa News

Cloud is not a country

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Medium and large businesses across South Africa, Kenya and Nigeria experience very different usage, benefits and intentions with cloud computing, according to new research by World Wide Worx and F5 Networks.

Cloud computing has taken off dramatically across Africa’s major markets, but its benefits are experienced very differently in each region – as are its budget allocations.

These were some of the key findings of Cloud Africa 2018, a research project conducted by World Wide Worx for global networking application company F5 Networks, across Kenya, Nigeria and South Africa earlier this year. Decision-makers at 300 medium and large organisations were interviewed about cloud computing usage, benefits and intentions.

“It is no longer about whether to use the cloud, but what benefits are being gained from the cloud,” says Matthew Barker, F5 Networks’ divisional sales manager for Sub-Saharan Africa. “These depend heavily on the dynamics of each market, so we were not surprised to see that businesses in each country emphasised different benefits.”

“Over the five years since World Wide Worx conducted equivalent research, use of the cloud among medium and large organisations has more than doubled, from less than 50% using it in 2013 to pervasive use in 2018”, says World Wide Worx managing director, Arthur Goldstuck.

Respondents in Nigeria and Kenya named business efficiency and scalability by far the most important benefit of cloud computing, with 80% and 75%, respectively, selecting it as an advantage, compared to 61% of South African respondents.

For South Africans, time-to-market or speed of deployment came in as the most prominent benefit, as cited by 68% of respondents. In contrast, only 48% of companies in Kenya and 28% in Nigeria named this as a key benefit.

Barker believes this is a result of the infrastructure challenges in developing information technology markets like Nigeria and Kenya, where the cloud is used to overcome the obstacles that get in the way of efficiency.

“In South Africa, with a more mature IT landscape, the focus is on the competition rather than the business itself,” he says.

This is borne out by the fact that almost a quarter (23%) of South African respondents see the cloud as a platform for international expansion, whereas this figure drops below one in five in Kenya (17%) and below one in ten in Nigeria (6%). The one area where all three countries are level – using the cloud as a platform for service innovation – is ranked exceptionally low, at around 15% across these markets.

“Internationally, it is taken for granted that the cloud is an ideal platform for both innovation and for establishing a global footprint,” says Goldstuck. “In these three markets, these are benefits that are only now beginning to be recognised, but are still a long way from being a priority. The cloud is here but its full benefits have not yet arrived.”

Key findings

Business impact:

·       82% of respondents in Nigeria have seen an impact from cloud computing on market share, with 48% seeing a high or very high impact.

·       In Kenya, 69% have seen an overall positive impact, while 48% had seen a high or very high impact on market share.

·       In South Africa, 66% had seen a positive impact but only 33% had seen a high or very high impact.

·       Innovation within the organisation saw an equally high impact in all markets, with 100% positive impact in Nigeria, 98% in Kenya and 88% in South Africa.

·       The cloud has had a similar impact on brand perception, at 100% in Nigeria, 98% in Kenya and 85% in South Africa.

·       The cloud has also had a high impact on customer experience, at 96% in Nigeria, 85% in Kenya and 81% in South Africa.

Cloud budgets:

Nine out of ten (90%) companies in South Africa said they had increased spending on cloud computing last year, and 83% said they would increase these budgets in 2018. In Nigeria, 78% said they had increased budgets last year, and 94% said they would increase their spending this year. The biggest increase comes from Kenya, however, with 74% of companies having increased cloud budgets in 2017, rising to a massive 98% in 2018.

A minimal proportion of respondents – not more than 2% in any of the countries surveyed – said they had decreased cloud spending last year. For 2018, no companies in Kenya or Nigeria said they would decrease spending, although 5% of South African respondents said they would.

Broken down by industry in South Africa, the highest proportion of increased budgeting for 2018 was reported by IT software and services companies, at 92%, followed by Mining at 85% and Retail trade at 83%. The biggest drop in cloud budgeting was expected by the Engineering sector, with 13% declining in planned spending.

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Apps:

When asked which apps were critical to organisations, 68% of Nigerian and 67% of Kenyan companies said Service apps were critical, while only 40% of South African respondents named these as key.

On the other hand, South African companies were far more likely than those in the other countries to regard human resources apps as important: 43% of South African respondents named HR apps as critical to business, compared to 19% in Kenya and 10% in Nigeria.

“It is clear that more attention is paid to internally-focused apps in South Africa than in the other markets,” says Barker. “In Nigeria and Kenya, on the other hand, customer-facing apps get the closest attention.”

A further indication of the low emphasis on internal apps is the rating of operational apps, which are seen as critical by only 15% of respondents in Kenya and 10% in Nigeria. While still low in South Africa, at 30%, it was more than double the proportion of the other two countries combined.

One area where all markets are equal, however, is in business apps, with only small variations between the three countries measured. Nigerian respondents took them slightly more seriously than the rest, with 76% seeing them as critical, while 72% of South African companies and 67% of those in Kenya agreed.

“Ultimately, the cloud is about better ways of doing business,” says Goldstuck. “That is reflected in cloud priorities and budgets across Africa.”

 

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