Knowledge-based computational models

Knowledge-based computational models

In our recent paper [1], we describe a biology-driven approach to translate cancer genomic data into clinically actionable information for personalized patient therapy selection. Despite the increasing knowledge on intracellular signal transduction pathways as drivers of tumor growth, and the corresponding development of a large number of " targeted drugs " to correct aberrant pathway behavior ...

Computational models of tacit knowledge

When an expert designer uses a term such as “interference fit" or “H7r6", they effortlessly invoke a rich set of associations across a wide range of experience. While at one level, the meaning of a termsuch as H7 is formally specified, many of these associations are implicitand hard to characterize formally. The explicit concepts build on layersof implicit abstraction; e.g. the concept of _t wo...

Validation of Computational Models Based on Multiple Heterogeneous Knowledge Sources

Theories of organizations have brought together multiple heterogeneous theories in computational models. In addition, in artificial intelligence, there has been an emphasis on the generation of knowledge-based systems that include multiple heterogeneous knowledge bases. As a result, increasingly, theory and model developers have called for the need to validate these computational models. Unfort...

Generation of human computational models with knowledge engineering

The Ambient Intelligence (AmI) paradigm envisions systems whose central entity is the user. AmI integrates technologies such as Artificial Intelligence, implicit Human Computer Interaction, and Ubiquitous Services. Each capability of AmI systems is oriented towards assistance of humans at work, in the classroom, or even at home. In consequence, the AmI development process usually incorporates t...

Revising Engineering Models: Combining Computational Discovery with Knowledge