Artificial Intelligence

81.

Temporal knowledge representation for scheduling tasks in clinical trial protocols.

Clinical trial protocols include detailed temporal constraints on treatment and associated tasks. Unlike health-care guidelines, protocols are highly prescriptive. Therefore, informatics applications that enforce such temporal constraints are more ...
Chunhua Weng, Michael Kahn, John Gennari (Proc AMIA Symp, 2002)
temporal-knowledge-representation-scheduling-tasks-clinical-trial.asp

82.

Defining medical concepts by linguistic variables with fuzzy Arden Syntax.

Diagnostic and therapeutic decisions in the domain of medicine usually depend on observed or measured data, such as observations made during an examination, or laboratory data. Furthermore, such decisions are often based on abstract domain knowledge. For ...
Sven Tiffe (Proc AMIA Symp, 2002)
defining-medical-concepts-linguistic-variables-fuzzy-arden-syntax.asp

83.

Computable decision modules for patient safety in child health care.

OBJECTIVE: To identify controlled evidence from the child health literature on patient conditions and clinical procedures that resulted in unacceptable adverse outcomes. METHODS: Systematic searches of MEDLINE (1966 to 2001), and Cochrane Database of ...
Ratna Pakpahan, E Andrew Balas, Suzanne A Boren (Proc AMIA Symp, 2002)
computable-decision-modules-patient-safety-child-health-care.asp

84.

Maximum entropy modeling for mining patient medication status from free text.

Using a classification scheme of patient medication status we sought to recognize and categorize medications mentioned in the unrestricted text of clinical documents generated in clinical practice. The categories refer to the patients status with respect ...
Serguei V Pakhomov, Alexander Ruggieri, Christopher G Chute (Proc AMIA Symp, 2002)
maximum-entropy-modeling-mining-patient-medication-status-free-text.asp

85.

An integrative model for in-silico clinical-genomics discovery science.

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery ...
Yves A Lussier, Indra Nell Sarkar, Michael Cantor (Proc AMIA Symp, 2002)
integrative-model-silico-clinical-genomics-discovery-science.asp

86.

Competence Center for Miniaturised Monitoring and Intervention Systems MOTIV.

In the national Competence Center, the whole value chain, from the idea to the development of a product ready for the market, is brought together. MOTIV has underlined three focus point: It wants to improve the therapy and therapy control, to develop ...
J U Meyer, G Müller, J Schmidt, H J Cappius (Biomed Tech (Berl), 2002)
competence-center-miniaturised-monitoring-intervention-systems-motiv.asp

87.

Towards a sharable numeric and symbolic knowledge base on cerebral cortex anatomy: lessons learned from a prototype.

We propose a knowledge base that combines numeric and symbolic knowledge about sulco-gyral brain cortex. This knowledge base is implemented using Web technologies. It is intended to be easily reusable in various application contexts such as teaching, ...
Olivier Dameron, Bernard Gibaud, Anita Burgun, Xavier Morandi (Proc AMIA Symp, 2002)
towards-sharable-numeric-symbolic-knowledge-base-cerebral-cortex.asp

88.

Natural language from artificial life.

This article aims to show that linguistics, in particular the study of the lexico-syntactic aspects of language, provides fertile ground for artificial life modeling. A survey of the models that have been developed over the last decade and a half is ...
Simon Kirby (Artif Life, 2002)
natural-language-artificial-life.asp

89.

Machine learning for sub-population assessment: evaluating the C-section rate of different physician practices.

We apply machine learning to the problem of subpopulation assessment for Caesarian Section. In subpopulation assessment, we are interested in making predictions not for a single patient, but for groups of patients. Typically, in any large population, ...
Rich Caruana, Radu S Niculescu, R Bharat Rao, Cynthia Simms (Proc AMIA Symp, 2002)
machine-learning-sub-population-assessment-evaluating-c-section-rate.asp

90.

Knowledge-based bioterrorism surveillance.

An epidemic resulting from an act of bioterrorism could be catastrophic. However, if an epidemic can be detected and characterized early on, prompt public health intervention may mitigate its impact. Current surveillance approaches do not perform well in ...
David L Buckeridge, Justin Graham, Martin J OConnor, Michael K Choy, Samson W Tu, Mark A Musen (Proc AMIA Symp, 2002)
knowledge-based-bioterrorism-surveillance.asp