A computer-based tool could help GPs to speed up the diagnosis and treatment of patients suffering from two of the most common forms of cancer, potentially saving thousands of lives every year.
Researchers at The University of Nottingham and ClinRisk Ltd have shown that the algorithm is successful in identifying those suffering with gastro-oesophageal cancer and lung cancer at an earlier stage by ‘red-flagging’ potentially worrying combinations of symptoms and risk factors.
Their results, published in the British Journal of General Practice on Monday October 31, showed that the 10 per cent of the patients that the algorithm predicted as most at risk of developing one of the two diseases accounted for 77 per cent of all the gastro-oesophageal and lung cancers diagnosed over the following two years.
Big data is, yes, about more data — the rising flood from corporate databases, Web browsing trails, sensors and social network communications. But it is just as much about speed.
If “big data” is more than a marketing term, it has to be the raw material for making smarter decisions, faster. And that means, as the big-data industry evolves, the need for groundbreaking new approaches to computing, both in hardware and software.
A simple example: the Watson question-answering computer that beat two human “Jeopardy!” champions earlier this year had to pore through vast quantities of data and come back with an answer in less than three seconds.
The speed requirement meant I.B.M.’s Watson had to do its near-instant data digging in memory instead of finding data on hard disks. Traditionally, memory chips surrounding the computer processor held the small amounts of data that had to be on hand for immediate tasks.
But getting answers quickly in the world of big data necessitates this new approach, called in-memory processing. “It’s a model for the future,” John E. Kelly, the head of I.B.M. research, said during an interview at Watson Labs.
With ample freshwater (including the nearby Great Lakes), rich agricultural land, and a cool climate, upstate New York was well positioned in a hot, thirsty, and oil-starved future. It was almost a Manifest Destiny. “It is our ecological responsibility to grow here,” he said.
Catherine Tumber would have agreed. Her excellent new book, Small, Gritty, and Green: The Promise of America’s Smaller Industrial Cities in a Low-Carbon World, finds potential in many busted and booming-again cities in the Northeast and Midwest, cities like Flint, Mich.; Muncie, Ind.; Peoria, Ill.; and Youngstown, Ohio. She could have swept south and also included Hagerstown, Md.; York, Pa.; and maybe even Richmond, Va.; and Greensboro, N.C., and still stuck to her thesis. Even my hometown of Baltimore — which might be larger but has so far avoided unchecked sprawl — may fit into Tumber’s vision. These places, she writes, are both big enough and small enough to manage a coming societal transition, in which people may have to live on constrained oil supplies and rely more on local networks for food and other goods.
Tumber’s thinking goes against the grain of urban thinkers who contend that cities will organize themselves into giant “megaregions,” sprawling into one another, often along interstates. (In this future, my hometown would be one node in a megalopolis that includes New York, Philadelphia, and Washington, D.C.) Megaregion futurism has its champions among pundits and policymakers: Richard Florida shuns smaller cities in the hinterlands with his theory of the “creative class” — society’s Alphas, who allegedly seek out cosmopolitan cities. Barack Obama’s $50 billion high-speed rail plan — which, for hefty ticket prices, would connect megaregions like Miami-Tampa, San Francisco-San Diego, and the Northeast Corridor — likewise ignores smaller cities, which would benefit from investment in regular old rail.
The megaregion concept is a product of globalization, which values ruthless efficiency and specialization, with most of the benefits going to elites. But Tumber believes that globalization is a historical anomaly, not necessarily a new world order. “Globalization relies on cheap, long-distance transportation and industrial food production, both highly dependent on finite reserves of oil, whose bounty is already belied by spiking fuel prices and mounting alarm about climate change,” she writes. Or, as put by James Howard Kunstler, the peak-oil prophet (whom Tumber cites here and there in her book): “The world is about to become a larger place again.”
So how do these small cities, long derided as provincial and irrelevant, prepare for the future that Tumber sees coming? She focuses on several broad topics: controlling sprawl and redeveloping the suburban fringe, developing agriculture in and around the city, reviving small-scale manufacturing, and redesigning economic networks and school systems. All of these topics involve interlocking policy conundrums that may be more easily navigated in small cities, where relationships are closer and bureaucracy less entangling.
Over the past couple of centuries, we have had a technology revolution every 40 - 60 years, starting with the Industrial Revolution in 1771, which was characterized by the emergence of machines, factories and canals. This was followed by the age of steam and coal, iron and railways which started in 1829; steel and heavy engineering (electrical, chemical, civil and naval) starting in 1875; and the age of the automobile in 1908. Our present information technology and telecommunications age, whose starting point Perez pegs at 1971, is the fifth such major revolution in that span.
Stock-outs of malaria treatments at the health facility level in many sub-Saharan African countries have been a persistent problem for many years. A stock-out is the unavailability of medicine at the health facility. In Tanzania, 93 % of the population are at risk for malaria infection. The number of malaria cases is estimated to be 11 million resulting into 60-80 thousand deaths per year or 220 deaths per day in Tanzania alone. The goal of the SMS for Life pilot project was to develop a flexible and scalable solution to bring up-to-date visibility of anti-malarials within the Tanzanian Public Health Sector with a potential to reduce or eliminate stock-outs of five drugs (four dosage forms of ACTs and Quinine Injectable) in all health facilities in a pilot sample of three districts.
Today’s morning keynote kicked off with Steve Mills talking about big data – “as if data weren’t big before”, he joked – and highlighted that the real challenge is not necessarily the volume of data, but what we need to do in order to make use of that data. A huge application for this is customer service and sentiment analysis: figuring out what your customers are saying to you (and about you), and using that to figure out how to deliver better service. Another significant application area is that of the smarter planet: sensing and responding to events triggered by instrumentation and physical devices. He discussed a number of customer examples, pointing out that no two situations are the same and that a variety of technologies are required, but there are reusable patterns across industries.
Doug Hunt was up next to talk about content analytics – another type of big data – and the impact on transforming business processes. He introduced Randy Sumrall, CIO of Education Service Center Region 10 (State of Texas), to talk about the impact of technology on education and the “no child left behind” policy. New technology can be overwhelming for teachers, who are often required to select what technologies are to be used without sufficient information or skills to do so; there needs to be better ways to empower the educator directly rather than just having information available at the administrative level. For example, they’ve developed an “early dropout warning” tool to be used by teachers, analyzing a variety of factors in order to alert the teachers about students who are at risk of dropping out of school. The idea is to create tools for completely customized learning for each student, covering assessment, design and delivery; this is more classical BI than big data. Some interesting solutions, but as some people pointed out on the Twitter stream, there’s a whole political and cultural element to education as well. Just as some doctors will resist diagnostic assistance from analytics, so too will some teachers resist student assessments based on analytics rather than their own judgment.
Next was Frank Kern to talk about organizations’ urgency to transform their businesses, for competitive differentiation but also for basic survival in today’s fast-moving, social, data-driven world. According to a recent MIT Sloan study, 60% of organizations are differentiating based on analytics, and outperform their competitors by 220%. It’s all about speed, risk and customers; much of the success is based on making decisions and taking actions in an automated fashion, based on the right analysis of the right data.
Some of IBM’s future of big data analytics is Watson, and Manoj Saxena presented on how Watson is being applied to healthcare – being demonstrated at IOD – as well as future applications in financial services and other industries. In healthcare, consider that medical information is doubling every five years, and about 20% of diagnoses in the US have some sort of preventable error. Using Watson as a diagnostic tool puts all healthcare information into the mix, not just what your doctor has learned (and remembers). Watson understands human speech, including puns, metaphors and other colloquial speech; it generates hypotheses based on the information that it absorbs; then it understands and learns from how the system is used. A medical diagnosis, then, can include information about symptoms and diseases, patient healthcare and treatment history, family healthcare history, and even patient lifestyle and travel choices to detect those nasty tropical bugs that your North American doctor is unlikely to know about. Watson’s not going to replace your doctor, but provide decision support during diagnosis and treatment.
IBM asked Forrester Research to examine how business leaders can create additional value beyond operational efficiencies and cost savings through their investments in information technology. We focused on social engagement, gaining strategic advantage and brand enhancement. The study is now complete.
Now we’re presenting the results in a Webinar, Not Your Father’s Total Cost of Ownership: Creating and Measuring the Expanded Value of IT, Thursday, Oct. 27, at 11 a.m. In the webinar we’ll also get additional perspectives on value from Steve Rogers of IBM’s Center for Applied Insights, and Dr. Andrew Watson, Director of the Center for Connected Medicine. It’s open to anybody who wants to participate. Register here.
Could 3D Printing Change the World? Technologies, Potential, and Implications of Additive Manufacturing explores the technology of AM and its broader implications, which include:
Assembly lines and supply chains could be reduced or eliminated for many products. AM can produce the final product—or large pieces of a final product— in one process.
Designs, not products, would move around the world as digital files are printed anywhere with any printer to meet design parameters. A “STL” design file can be sent via the Internet and printed in 3D.
Products could be printed on demand without the need for inventories.
A given manufacturing facility would be capable of printing a huge range of products without retooling—and each printing could be customized without additional cost.
Production and distribution of material products could become de-globalized as production is brought closer to the consumer.
Manufacturing could be pulled away from “manufacturing platforms” like China back to the countries where the products are consumed, reducing global economic imbalances as export countries’ surpluses are reduced and importing countries’ reliance on imports shrink.
The carbon footprint of manufacturing and transport as well as overall energy use in manufacturing could be reduced substantially and thus global “resource productivity” greatly enhanced and carbon emissions reduced.
Reduced need for labor in manufacturing could be politically destabilizing in some economies while others, especially aging societies, might benefit from the ability to produce more goods with fewer people while reducing reliance on imports.
The United States, the current leader in AM technology, could experience a renaissance in innovation, design, IP exports, and manufacturing, enhancing its relative economic strength and geopolitical influence.