Abstract: A system for generating image-based patient profiles acquires digital images from tissue samples and CT and MRI scans. The system detects objects within the images, measures values related to the detected objects, and displays the measured values in patient profile lists that indicate the normal ranges for measured values. The system indicates which measured values fall outside the normal ranges and navigates the user to the objects in the images associated with the abnormal values when the user selects a measured value in the patient profile. Various risks of the existence of different diseases and the probability of success of specific treatments are displayed on a graphical user interface. The system searches for patterns in the patient data and profile lists that reflect those specific risks and success probabilities. A high probability of disease risk or of the success of a specific treatment is indicated on the graphical user interface.

Abstract: A method is disclosed for extracting information from input data comprising mapping of the input data into a data object network. The method uses a semantic cognition network comprised of the data object network, a class object network and a processing object network. The semantic cognition network uses a set of algorithms to process the semantic units. The semantic cognition network defines a processing object in the processing object network by selecting a data domain in the data object network, a class domain in the class object network and an algorithm from the set of algorithms. The processing object comprises the data domain, the class domain and the algorithm. The processing object is used in the processing object network to process the semantic units.