AIM, Artificial Intelligence in Medical Applications



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AI techniques have valuable benefits to offer medical systems. Techniques such as abstraction, conceptualization (of sensor data), Semantic Nets, Case-Based Reasoning (CBR), Clustering, and User Modeling have been used to develop theories and a system that is able to classify complex medical measurements from a person that may need preventive actions and treatment for stress problems. The developed method and techniques are able to classify individual sensor data that can be used for a final classification of a person. Hearth rate variability, finger temperature, conductance, breathing and CO2 level are the measurements used in this clinical diagnosis process.

Peter Funk, Professor

Room: U1-126
Phone: +46-21-103153