scholarly journals Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction

2005 ◽  
pp. 86-96 ◽  
Author(s):  
Doug Fisher ◽  
Mary Edgerton ◽  
Lianhong Tang ◽  
Lewis Frey ◽  
Zhihua Chen
Keyword(s):  
Rule Induction ◽  
Backward Chaining ◽  
Feature Interactions

scholarly journals Backward chaining rule induction

2006 ◽  
Vol 10 (5) ◽  
pp. 397-417 ◽  
Author(s):  
Douglas H. Fisher ◽  
Mary E. Edgerton ◽  
Zhihua Chen ◽  
Lianhong Tang ◽  
Lewis Frey
Keyword(s):  
Rule Induction ◽  
Backward Chaining

scholarly journals Data Mining for Gene Networks Relevant to Poor Prognosis in Lung Cancer via Backward-Chaining Rule Induction

2007 ◽  
Vol 3 ◽  
pp. 117693510700300
Author(s):  
Mary E. Edgerton ◽  
Douglas H. Fisher ◽  
Lianhong Tang ◽  
Lewis J. Frey ◽  
Zhihua Chen
Keyword(s):  
Lung Cancer ◽  
Data Mining ◽  
Gene Networks ◽  
Rule Induction ◽  
Learning System ◽  
Gene Expression Array ◽  
Task Sequence ◽  
Expression Array ◽  
Backward Chaining ◽  
Survival Status

We use Backward Chaining Rule Induction (BCRI), a novel data mining method for hypothesizing causative mechanisms, to mine lung cancer gene expression array data for mechanisms that could impact survival. Initially, a supervised learning system is used to generate a prediction model in the form of “IF <conditions> THEN <outcome>” style rules. Next, each antecedent (i.e. an IF condition) of a previously discovered rule becomes the outcome class for subsequent application of supervised rule induction. This step is repeated until a termination condition is satisfied. “Chains” of rules are created by working backward from an initial condition (e.g. survival status). Through this iterative process of “backward chaining,” BCRI searches for rules that describe plausible gene interactions for subsequent validation. Thus, BCRI is a semi-supervised approach that constrains the search through the vast space of plausible causal mechanisms by using a top-level outcome to kick-start the process. We demonstrate the general BCRI task sequence, how to implement it, the validation process, and how BCRI-rules discovered from lung cancer microarray data can be combined with prior knowledge to generate hypotheses about functional genomics.

Das Aufstehen trainieren – Die Backward-Chaining-Methode

physiopraxis ◽  
2020 ◽  
Vol 18 (04) ◽  
pp. 44-47
Author(s):  
Rebekka Leonhardt ◽  
Michaela Groß
Keyword(s):  
Ältere Menschen ◽  
Backward Chaining

Nicht alleine vom Boden aufstehen zu können, hat für ältere Menschen nach einem Sturz schwere Folgen: Gesundheitliche und funktionelle Einschränkungen verschlechtern sich bis hin zur erhöhten Mortalität. Die Backward-Chaining-Methode hilft in der Therapie dabei, das sichere und unabhängige Aufstehen zu erlernen und Sturzangst zu mindern.

Expert System: Vertigo Disease Diagnosis with Backward Chaining Method

2020 ◽  
Author(s):  
Beki Subaeki ◽  
Shinta Getri Lovelina ◽  
Hanhan Hanafiah Solihin ◽  
SW Pitara ◽  
Ahmad Munandar ◽  
...  
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Backward Chaining
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