Data without science is nothing; just 1s and 0s, floating around a cloud waiting for someone to make sense of them. Data science is the process of extracting value from data, using advanced analytics tools. Enormous amounts of health information are being gathered every second, and we are rapidly getting better at decoding it: turning bytes into insights that can be used to improve the lives of patients. But the pace, methods and ethics of data science adoption varies dramatically between countries and regions. Why should we care about keeping up?
Data science is all about creating value from data using advanced new tools. In the health sector, that means creating value for the patient. It enables the extraction of information that can’t be accessed with normal statistics, either because the data sets are too big, disordered, or qualitative instead of quantitative (e.g., with health records or medical imaging).
By bringing together AI tools – such as machine learning, natural language processing and advanced analytics – data science can create new insights, increase efficiency, and smooth processes in the health sector. Many countries around the world are already embracing this evolution in health science, and for good reason!
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