|Doctors performing a surgery. / Photo by: Getty Images|
Physicians are increasingly turning to big data to help them treat complex diseases such as cardiovascular diseases and dementia. Big data involves the analysis of factors such as people’s lifestyles, genes, and medical records to develop personalized treatment, according to Gary Finnegan, writing for the Horizon Magazine.
Cardiovascular diseases can be difficult to treat because they are caused by a combination of genetic and lifestyle factors, making it very hard to predict results and decide the most suitable therapy for any patient. Professor Folkert Asselbergs from the University College London and scientific lead for the BigData @ Heart project, stated that the relative roles played by genetics and risk factors such as exercise and diet have not yet been fully explained in hypertension, diabetes, and kidney diseases. Professor Asselbergs added that this complicates predicting a patient’s prognosis.
Developing prognosis algorithms using machine learning and data mining is the mandate of the BigData @ Heart project. It employs a system that makes use of a patient’s medical history, together with the hospitalization rates and country-specific statistics for similar patients to create the most effective treatment regimen.
Fast-paced innovations in computing power will enable scientists to exploit the benefits of big data in studying the causes of poor health, most-probable results, and the most potent treatment methods for certain illnesses. Such technological breakthroughs will also pave the way for the evolution of elaborate algorithms that are capable of analyzing data on genetics, lifestyle, and other health issues. Such a scenario could lead to the era of individualized and efficient patient care.
Professor Rick Grobbee, the overall lead of the BigData @ Heart project, claimed they have access to most of the big European cardiovascular databases such as those dealing with electronic health records and disease registries to clinical trials and large epidemiological cohorts. As such, they can retrieve data on 5 million cases of atrial fibrillation, heart failure, and acute coronary syndrome, as well as the health information of over 16 million healthy individuals.