Health Informatics Journal · 2015 · 69 citations · 15 references
ComputingHealth InformaticsNursing InformaticsArtificial IntelligenceClinical Decision SupportData MiningClinical Decision Support SystemsDecision Support In HealthcareDiagnostic Decision SupportArtificial Intelligence-assisted DiagnosisClinical Data MiningDecision Support In DiagnosisDiagnostic Accuracy StudiesDiagnostic Prediction ModelsFuzzy Inference SystemsKnowledge-based Diagnosis
This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics.
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R. Brian Haynes, Nancy L Wilczynski · Implementation Science · 2010 · 153 citations · Full text
Computing, Health Informatics, Clinical Decision Support +16