Clinical Practice Knowledge Acquisition and Interrogation using Natural Language

• Author(s): Mendes, David
• Date: 2015
• Persistent ID: http://hdl.handle.net/10174/12553
• Origin: Repositório Científico da Universidade de Évora
• Subject(s): Knowledge Acquisition; Knowledge Interrogation; Clinical Ontology
• Document Type: Doctoral thesis
• Language: Portuguese

Description

The scientific concepts, methodologies and tools in the Knowledge Representation (KR) sub- domain of applied Artificial Intelligence (AI) came a long way with enormous strides in recent years. The usage of domain conceptualizations that are Ontologies is now powerful enough to aim at computable reasoning over complex realities. One of the most challenging scientific and technical human endeavors is the daily Clinical Prac- tice (CP) of Cardiovascular (CV) specialty healthcare providers. Such a complex domain can benefit largely from the possibility of clinical reasoning aids that are now at the edge of being available. We research into a complete end-to-end solid ontological infrastructure for CP knowledge represen- tation as well as the associated processes to automatically acquire knowledge from clinical texts and reason over it.