Importance of data and data science
These days doctors use many different types of diagnostic tests and medical procedures such as MRI, CT, ECG, EEG, colonoscopy, etc., to obtain the final diagnoses for their patients. For the past few decades, all this data from these medical devices along with patients' final diagnoses are being stored and by now, diagnostically speaking, an enormous amount of successfully solved medical cases have been collected. Doctors usually order blood tests for their patients to obtain even deeper insight into their health. Blood tests are especially popular because they are non-invasive, easily accessible, and cheap, but at the same time, they reveal a great deal about our inner homeostasis. It is estimated that more than 14 billion blood tests are ordered every year.
Today doctors usually use reference intervals of individual blood parameters to interpret a patient’s health. But what if the blood parameters are within their normal ranges, but the patient is still ill? Unfortunately, interpretation of all these blood parameters, especially their interactions, is simply unfeasible even for the best medical experts. While the human brain is not capable of recognizing patterns in such vast amounts of data, it would be unreasonable to conclude that these patterns are not there. Data science and machine learning have evolved out of statistics specifically to tackle this kind of task. With the help of modern computers, data science allows us to process and transform these large data collections in order to gain a better insight into the underlying patterns within the data. It allows us to draw conclusions from those patterns, as well as to build and use probabilistic models that are capable of making predictions about newly observed data.
Even though data science and machine learning are far from new, they are rapidly gaining popularity because of the availability of much more data and the improvement in computing power which makes it easier to process and analyze these large data collections. As the real value of data is being recognized, the demand for data science has never been greater and will continue to increase.
At Smart Blood Analytics Swiss SA, we understand the importance of data, and that is why we focus our development on building models based on extensive data collections of successfully solved medical cases. This means that our models are capable of coming to the same diagnostic conclusions as the doctors that solved these cases.