Time Series Data Used for Diseases Recognition and Anomaly Detection

For now, the data we used were static. There is a group of sets where the data change over time. One of such examples is the sound. When we take a CT scan, we receive a set of images, but the set is a capture of a small piece (slice) of our body. It is even possible to combine the MRI slices into a 3D model as the distance between the slices is fixed. A different approach is proposed in videos, such as ultrasound videos, in which we see changes in an organ, usually in a short period of time. The time series usually does not rely on images only but, in most cases, on sets of tabular sets. We can observe how the observed organ changes its behavior over time, making it possible to recognize different types of anomalies or diseases compared to data captured in one time, such as typical MRI scans.