Published By : 20 Jun 2018 | Published By : QYRESEARCH
Big data is primed to revolutionize a number of sectors by making sense of figurative information that organizations produce but until now weren’t using them for their benefit. However, the healthcare industry needs to be little more careful when it comes to depending on big data for understanding human health and behavior, according a group of researchers from the University of California. The study has suggested that each individual is different and clinical trials should move beyond generalizing big samples of subjects.
The findings have questioned the accuracy or reliability of big data because moments and personalities determine human behaviors, emotions, and physiology, and hence it is not logical to average out data from a collection of large groups of subjects. The study is expected to change the way data is mined from social media to formulate customized therapies.
According to Aaron Fisher, the leading author of the study – it is imperative that individuals are studied rather than groups of them when it comes to understanding their health and feelings. A number of mental disorders, diseases, behaviors, and emotions construct a person over time and studying one instance is not adequate to capture these phenomena.
The study has highlighted that advanced technologies are enabling humongous data collection and modern computing has the ability to compile data from individuals and make useful determinations. As many as six distinct segments of data was analyzed, including smartphone self-report surveys and online. The results showed that there was a consistency in errors with group data not being true to individuals.