Medical and biology data are among the most data analyzed and treated. Biological and medical experimentations in vitro are very expensive, because they are characterized by their complexities and big volumes and results are very sensitive about the health of human. Thus, the exploitation of new technologies and computer science models becomes a necessity, firstly to reduce the cost of experimentations and secondly to help experts (doctors and biologists) to make the good decision. The virus Covid’19 is a good lesson and motivation for humanities to continuously develop technologies and computer science programs. In fact, predict diseases or the severity level of virus before any diagnostics become a real challenge for our society and for many researchers from various disciplines (Biology, Medicine, Statistics, Computer Science, etc.).
Today, there are many processes used for processing data in order to deal with many real-world issues, such as classification, prediction, regression and clustering. The main goal of these processes is to discover knowledge from data in order to make a precise decision. Also, in this kind of problems, the tolerance of errors rate is very low, because the decision concerns the health of human. In addition, it is a challenge for researchers to propose their optimal works in short time. Since many decades, researchers try to win dangerous diseases, while not neglecting the fact that research in this regard is developing from day to day.
The main goal of the DSSBH2023 special session is to present the recent researches, and their results, on data sciences techniques for the analysis of biology and healthcare data. This session provides a more focused, in-depth venue for presentations, discussions and interactions of a very important subject.