Biomedical Artificial Intelligence

This talk will survey the intriguing connections between artificial intelligence and its biomedical application domain. Biology has recently become a data- rich, information hungry science because of recent massive data generation technologies, but we cannot fully analyse this data due to the wealth and complexity of the information available. The result is a great need for intelligent systems in biology. We will visit examples such as machine learning for pharmaceutical drug discovery, optimal heuristic search for protein structure prediction, rule-based systems for drug-resistant HIV treatment, constraint- based design of large self-assembling synthetic genes, and a multiple- representation approach to curing some forms of cancer. The talk will conclude with suggestions for how AI practitioners can begin the explore this rich and fascinating domain.

Authors and Affiliations

1. Information and Computer Science, University of California, Irvine, CA, 92697-3425, USA

   Richard Lathrop

Editors and Affiliations

1. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

   Chengqi Zhang

2. Department of Computer Science, Auckland University of Technology, 1020, Auckland, New Zealand

   Hans W. Guesgen

3. Artificial Intelligence Technology Centre, Auckland University of Technology, Auckland, New Zealand

   Wai-Kiang Yeap

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© 2004 Springer-Verlag Berlin Heidelberg

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