After falling victim to an extremely rare kind of vocal chord paralysis that’s preventing him from giving the kind of long-winded keynote speeches we’re used to hearing from CEOs, Google’s Larry Page has announced a plan to gather data from people suffering from similar conditions. His hope is that by crowdsourcing the limited amount of data that exists about this condition, researchers will be able to come up with better ways for treating it, and maybe even a way to prevent it happening in the first place.

Page’s call to action made headlines precisely because of who he is, but this kind of crowdsourced approach has actually been popular for a while. In fact, it’s one of the most visible ways in which Big Data is helping us to gain a better understanding of the more bewildering health problems impacting people’s lives today.

From relatively benign conditions like the common cold, to more serious problems like dealing with Cholera epidemics and Parkinson’s disease, crowdsourced Big Data is fast becoming one of the most powerful tools to help us eradicate diseases around the world.

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Health eHeart’s In The Right Place

Heart disease isn’t a rare phenomena, far from it. In fact, it has the annoying habit of cropping up in our lives all too often, claiming something like 600,000 of them every year in the United States alone. Medical professionals have been trying to reduce this figure for years, but no matter what kinds of drugs they develop to treat the disease, the biggest problem is that people don’t help themselves – so many of us lead unhealthy lifestyles, that a certain amount of heart disease is almost inevitable.

But the scientists aren’t giving up. Recently, a team from the University of California in San Francisco launched one of the most ambitious Big Data research projects ever conceived – known as the Health eHeart study, the researchers have created a smartphone app that will gather data including heart rates, blood pressure, activity levels, ECG, sleep patterns and more from an astonishing one million people over the next ten years.

Interestingly, they won’t be studying anyone who already has a heart condition. The goal is not to study the disease itself, but rather the kinds of lifestyle choices that ultimately cause it to happen. They’re in it for the long haul, but within the next decade we’ll be able to find out exactly what causes heart disease, what kind of person is most likely to suffer from it, and perhaps, start saving a few more lives.

Predicting Disease Epidemics

People are a fantastic source of data, but they’re not the only source. Historical data can often be just as valid, especially when we’re looking for clues that could help us to prevent nasty outbreaks of disease. Medical experts have known all along that the clues to preventing disease are there, but until recently we’ve just never had the resources we need to find them.

Enter Kira Radinsky at Microsoft Research to change all that. The young Israeli PhD graduate made headlines earlier this year when she helped to develop data mining software that’s able to predict just about any kind of disaster you could care to imagine – not just disease outbreaks, but famine, war, earthquakes, tsunamis and other dozens of other natural catastrophes.

Radinsky’s software works by chomping its way through thousands of media sources, including digital newspaper clippings, news websites and other online sources, hunting for correlations with specific events. To cut a long story short, her software was able to correctly predict two separate outbreaks of cholera; one in Angola in 2006, and a more recent one in Cuba, simply through identifying the kinds of news reports that are likely to precede such an event.

Picking Away at Parkinson’s

Parkinson’s doesn’t claim anywhere near as many victims as heart disease, and neither does it bring about the kind of devastation and suffering that epidemics do. Nevertheless, it’s an extremely debilitating degenerative disorder that seriously impacts the lives of anyone unfortunate enough to suffer from it.

There’s an awful lot that doctors don’t understand about Parkinson’s disease, which means that even though it was first identified in 1886, they’ve been unable to come up with any kind of cure. To try and crack the problem, The Michael J. Fox Foundation (MJFF) has just begun exploring how data collected from mobile phones might be able to help doctors get a better understanding of the disease.

To do so, MJFF has teamed up with a company called LIONSolver, which has created machine learning software to help it analyse the data collected from Parkinson’s sufferer’s mobile phones. Drake Pruitt, CEO of LIONSolver, explains:

“The dream is a physician would have a way of monitoring the daily life of patients. Parkinson’s disrupts the daily life of people 24 hours a day, but a patient would only see their doctor once a month or once a quarter. It’s a challenge to accurately recap what’s happened — if they’re feeling great, it’s been great and if they’re feeling poorly, it’s been horrible and the reality is somewhere in between. To enable a physician to see what’s really going on is something the physicians are very excited about, and patietns as well. We’ve talked to physicians who are really excited by this possibility.”

They’re not overly optimistic of a cure just yet. So little is understood about what causes Parkinson’s that we’re probably years away from eradicating it, but by gaining a better idea of how the condition impacts people’s lives and how it progresses, we’ll definitely move closer towards that goal.