Digital transformation has been a buzzword in many industries, including healthcare, for several years. The application of data intelligence is a key component of this transformation, particularly in the medical science field. Data intelligence in healthcare refers to the analysis and interpretation of data collected from various sources such as medical records, clinical trials, and patient-generated data. In this blog, we will discuss the use cases of data intelligence in medical science, the problems it solves, and the statistics and facts associated with it.

Understanding the basic problem

One of the biggest problems in medical science is the vast amount of data that is generated every day. Traditional methods of data analysis are time-consuming and cannot keep up with the volume and complexity of data. Data intelligence solves this problem by using machine learning and artificial intelligence algorithms to analyze large datasets quickly and accurately. This is like using a microscope to look at the stars – the traditional methods of data analysis would take too long to be effective, but with data intelligence we can make sense of it all quickly and accurately, just like a microscope allows us to see the stars in all their detail.