Healthcare in the 21st century is at an impasse. Like so many things, it is a case of limited supply and unlimited demand, and the gap between the two is growing ever wider. Residents of the UK fear that the National Health Service (NHS) will undergo privatisation. Divided up piece by piece and flogged to the highest bidder. In the US, President Obama is trying to make affordable healthcare a reality for all Americans, but it is proving an uphill struggle. The number of people losing their lives to diseases still vastly outweighs the number of survivors. There could be a solution though. Organisations are starting to use Data Science to try and track, diagnose and even cure some of the world’s most widespread diseases. We have compiled 3 of the most common diseases suffered worldwide and the ways in which Data Science is being used to save lives.
The C Word
San Francisco start-up Enlitic are training deep learning algorithms to detect the early warning signs of cancer much quicker than a doctor could. This means the diagnosis is more efficient, and we can administer treatments quicker. Elsewhere, the Oregon Health and Science University are trialling gene-mapping as a possible solution. They aim to map the gene sequences of thousands of cancer patients in order to understand how the cancers form. This also ensures fast diagnoses. In fact, the institution has made the ambitious claim that it would like to offer same-day cancer diagnosis by 2020. This may seem like a bold statement, but it clearly shows the faith they have in using Data Science to this end.
Parkinson’s Disease
A condition that has an inextricable hold over 5 million people worldwide, with over 1 million of those living in the US, is Parkinson’s Disease. Doctors epitomise this neurological condition by the physical tremors many patients suffer from. Unfortunately, by the time this motor-based symptom appears, much of the damage is already done. Before visible symptoms appear, as much as 80% of the Dopamine cells in the brain are already lost. More frighteningly for those suffering from the condition, there is no known cure. While there is no cure for Parkinson’s at present, researchers are looking at how we can use data science for this condition.
There is a possibility we could detect Parkinson’s symptoms in those who might have a predisposition. They simultaneously aim to make life easier for those who are already afflicted with the condition. Several firms want to use the Internet of Things to help Doctors better understand Parkinson’s symptoms. This includes the aforementioned tremors, walking gait and sleep quality. To this end, Intel has partnered with the Michael J Fox Foundation to develop a series of wearable technologies. They will alert the wearer that they might have a predisposition to the condition. The wearables will also be able to upload their data to a central hub, from which data scientists and doctors will be able to analyse and study the data. This will help them to identify common threads amongst patients to one day find a cure for Parkinson’s.
Ebola
A third condition, which has burst into the public consciousness in the last five years, is Ebola. Between March 2014 and October 2015, there were over 10,000 reported cases in West Africa alone, which resulted in some 5,000 deaths. The disease’s focal point is Guinea, Liberia and Sierra Leone. They happen to be three of the poorest countries in the world, and the disease is spreading at an alarming rate. This exacerbates the crisis.
So where does data science come into this? We can track the infection across Africa, in order for aid workers and doctors to know where to send aid to most urgently. The Centre for Disease Control (CDC) is utilising real-time mapping software and telecommunications masts to track the disease across Western Africa. When there is a flare-up in one part of the country, and the threat of infection raises significantly, the CDC can send resources to the area to try and limit the spread.
In addition, pharmaceutical firm Pfizer has been looking at how to limit the spread of infection. In the past, Pfizer used Big Data to investigate how HIV declined in Scandinavia. It transpired that some people produced antibodies that made them more resistant to the disease. Pfizer was then able to replicate the genetic makeup of this antibody and use it in their treatments of HIV. Tim Gamble, who headed up the Pfizer team when they made this discovery, has not ruled out a similar path for Data Science in the fight against the spread of Ebola.
We cannot say for definite that Big Data will be able to stop the spread of Ebola. However, it will vastly improve the spread of resources to areas that need them the most.
Can Data Science Stop Disease?
Data Science could have a huge impact on diagnoses for diseases, as well as tracking and treatment worldwide. But it does come with its own challenges. Medical data is personal property, in other words confidential. Thus, it is not accessible to others without consent from the individual. This presents huge difficulties for companies using machine learning, which require a large pool of data to train from. Although these companies are fighting hard to gain blanket permissions to access medical data, it is ultimately up to the patients. Furthermore, whilst there are obvious capabilities with Big Data, can data science ever be able to find a cure for any of these conditions? One might also question whether, in the future, Data Scientists and Doctors will be of equal importance to the diagnosis and eventual recovery of a patient, despite many Data Scientists have little to no medical experience or training?
Data Science and healthcare could be a match made in heaven. It offers enormous opportunity to tackle some of the deadliest diseases head-on. It does, however, need the collaboration of patients and medical professionals. We could of course follow the suggestion of TED speaker John Wilbanks. In his 2012 talk, he suggests we pool our medical data. This will provide Doctors and Data Scientists with a larger spectrum of data to research. This gives us all the best chance of diagnosing, treating or even preventing these conditions before they can take any more lives.
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