Motivation:

Computational intelligence (CI) techniques have been recently more often applied in medical decision support. However, there is often very little communication between researchers in CI and those working in the medical field. This session aims at bridging the communication gap between CI and medical researchers by increasing the CI researchers’ understanding on the requirements and challenges imposed in medical diagnosis as well as by increasing the medical researchers’ understanding of modern CI algorithms.

The special session’s scope includes topics such as design of computer-aided diagnosis (CAD) systems in medicine with an emphasis on medical imaging. Researchers from both computational intelligence as well as medical fields are invited to submit papers.

Scope:

• Classifier design for medical decision problems (specifically neural-network based classifiers)
• Computational intelligence techniques in medical image processing
• Clinically relevant criteria of evaluating neural network-based and other decision support systems
• Data handling schemes for computer-aided decision systems evaluation
• Impact of training parameters such as number of examples and class prevalence on the classification performance of neural networks-based and other classifiers for computer-aided medical diagnosis
• Computational intelligence and machine learning algorithms to improve performance and optimize databases of examples for case-based computer-aided medical decision systems
• New applications of computational intelligence algorithms to decision support systems in medicine.

Special Session Chairs: