In business we measure how useful something is by either the money it saves, or the profit it generates, but how important is Money when it comes to making a difference? We hear terms such as ‘revolutionary’ with almost every new product launch, but never has the term been used more appropriately than when discussing Big Data’s effect on Healthcare.
The American Society of Clinical Oncology (ASCO) estimates that by 2025, demand for oncology services will grow by 42%, while the supply of oncologists will grow by only 28%, creating a shortage of more than 1,487 oncologists.
Oncologists are responsible for administering a variety of treatments such as Chemotherapy and Immunotherapy, but the basis of their role is to discuss with the patient, the best treatment options. With over 300,000 new cases of Cancer diagnosed every year in the UK alone, Cancer brings a huge pressure on valuable resources, often stretching Oncologists.
So how can Big Data and Analytics relieve the strain on Oncologists, and aid them in tailoring a treatment to an individual patient?
In fact, with the help of Cognitive Computing, it is already doing just this.
The need for Cognitive Computing lies in the fact that much of the ‘Big Data’ being created every second is unstructured, in the form of pictures, videos and text. Here, an intelligent computing system is needed to mine, and make sense of all the increasingly available data. Without such a system, the data is worthless.
Cognitive systems around the world are currently being fed large quantities of health data in the form of peer-reviewed journals relating to prostate, lung and breast Cancer. This allows the system to, not only draw upon a breadth of knowledge and experience unreachable for a fully trained Oncologist, but draft opinions, actions and hypotheses, similar to that of a human being.
But why is this important?
Traditionally, in an attempt to assign the correct treatment, highly skilled doctors would sequence both the patients Genome and the Cancers DNA, a process that can take weeks or even months. Second to this is that bias and human error can corrupt an otherwise informed decision. Cognitive Computing has the power to dramatically decrease sequence times whilst providing the doctors with all the information they need, without bias or error, in order for them to make to most informed decision possible.
So what does all this mean? Will Cognitive systems soon replace the need for highly trained Doctors and Oncologists? It’s unlikely we will ever see a computer acting independently in that way, despite what Hollywood would have you believe, but it is very realistic to expect a computers ‘opinion’ will influence a humans.
I am in no doubt that the next breakthrough in Oncology will in part be down to Big Data and Cognitive Computing.