In a defense / homeland security scenario, an intelligence officer have to sift through vast amounts of soft information in the form of text transcriptions of witness statements and expert reports and merge them with hard data from different types of sensors in the generated battlefield decision.
These methods can useful in many different contexts, for example, in a medical setting and hard evidence from different, a doctor can be a both soft evidence, such as text transcriptions of the patient analyze statements and text from expert opinions in journals sensor – based data such as blood pressure readings – to render judgment on a course of treatment.. Blending different kinds of data may very difficult and time consuming, explains Kamal Premaratne, professor in the UM Department of Electrical Engineering and computer science , and lead principal investigator of this project. In many applications, the amount of soft and hard data enormous, overwhelming at times people make sense of the information needs Consequently, there is interest in developing automated methods to extract meaning from the data and be able to detect hidden patterns and trends.Its work has focused on the development of lab activities for clinical diagnostics and therapy follow in Alzheimer s disease. Have significant effects both drug discovery and patient treatment ‘the field of brain diseases, In the future, biomarkers, the possibilities for early diagnosis and treatment of increase which measuring effects ‘Blennow said on 23rd ECNP Congress in Amsterdam, Netherlands. ‘In the future, this might enable physician for diagnosing and treating Alzheimer’s disease, before the person experiences no symptoms. ‘.