A case-based apprentice that learns from fuzzy examples
Methodologies for intelligent systems, 5
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Case-Based Learning of Strategic Knowledge
EWSL '91 Proceedings of the European Working Session on Machine Learning
A Reflective Architecture for Integrated Memory-Based Learning and Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Case-Based Reasoning in the Care of Alzheimer's Disease Patients
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Integrating Different Methodologies for Insulin Therapy Support in Type 1 Diabetic Patients
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Case-Based Reasoning in CARE-PARTNER: Gathering Evidence for Evidence-Based Medical Practice
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Prognostic Model for Early Warning of Threatening Influenza Waves
Proceedings of the 1st German Workshop on on Experience Management: Sharing Experiences about the Sharing of Experience
Combining case-based and rule-based reasoning: a heuristic approach
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Aggregating features and matching cases on vague linguistic expressions
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
A multi-module case-based biofeedback system for stress treatment
Artificial Intelligence in Medicine
International Journal of Hybrid Intelligent Systems
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Increased exposure to stress may cause health problems. An experienced clinician is able to diagnose a person's stress level based on sensor readings. Large individual variations and absence of general rules make it difficult to diagnose stress and the risk of stress-related health problems. A decision support system providing clinicians with a second opinion would be valuable. We propose a novel solution combining case-based reasoning and fuzzy logic along with a calibration phase to diagnose individual stress. During calibration a number of individual parameters are established. The system also considers the feedback from the patient on how well the test was performed. The system uses fuzzy logic to incorporating the imprecise characteristics of the domain. The cases are also used for the individual treatment process and transfer experience between clinicians. The validation of the approach is based on close collaboration with experts and measurements from 24 persons used as reference.