Constantinos Koutsojannis (EDT) Medical Knowledge Extraction from Big Data

Annotation

Data mining refers to the activity of going through big data sets to look for relevant information. As human health care data are the most difficult of all data to collect and their primary direction is the treatment of patients, and secondarily dealing with research, almost the only vindication for collecting medical data is to benefit the disease. All data miners should take into account that Medical Knowledge Extraction is internally connected with the Evidence-Based Medical approach because it uses data for already treated or not patients and there are times that opposites to Guideline Based medical practice. Additionally, all researchers should be aware when are dealing with medical databases they may face the possibility that their work will never be accepted or even used from health care professionals if all these obligations will not be correctly addressed from the early beginning. In the present book, one can find after the three introductory chapters, a number of successfully evaluated applications that have been developed after mining approaches in big or smaller amount (according to the application) of medical Data in different fields of every day clinical practice from teams of experts. The challenging adventure of Medical Knowledge Extraction can be followed by ambitious researchers finally resulting in a successful decision support system, that sometimes is so novel that it will provide new directions for basic or clinical research further that the existed. At least this procedure will save the experience of the best doctors on duty and will help young residents to be better and better.